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OPENNLP-1888: Document annotation container with typed offset-anchored layers - #1182

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OPENNLP-1888-DocumentShape
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OPENNLP-1888: Document annotation container with typed offset-anchored layers#1182
mawiesne merged 38 commits into
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OPENNLP-1888-DocumentShape

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@krickert

@krickert krickert commented Jul 17, 2026

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Adds the document annotation container discussed on OPENNLP-1888 and on the dev list in July.

Purpose. The task APIs each return one kind of result. An application that runs several over one text has to align them itself, and results that refer to other results (coreference chains, dependency arcs) have no place to live. Document is that place: the original text plus typed annotation layers over it. It is additive and replaces none of them.

Shape. Four types in opennlp-api, package opennlp.tools.document:

  • Document: the text, get(LayerKey<T>), with(LayerKey<T>, List<Annotation<T>>), layers(). Immutable; adding a layer returns a new document.
  • Annotation<T>: a Span into the original text and a value.
  • LayerKey<T>: id, value type, and scope (positional or document). Toolkit ids use the opennlp: prefix; extensions use their own; gold: marks a hand-annotated version of a layer.
  • DocumentAnnotator: annotate, requires, provides. DocumentAnalyzer checks the declarations when the pipeline is built.

What gets attached. Adapters over the existing components provide opennlp:sentences, opennlp:tokens, opennlp:pos, opennlp:lemmas, opennlp:stems, opennlp:entities, opennlp:chunks, and opennlp:phrases; the manual chapter has the table with value types and span anchors. The container knows none of these keys, and a new layer needs no change in the package (DocumentContractTest.testCustomLayerNeedsNoContainerChange).

Rules, each pinned by a test in DocumentContractTest: key equality is (id, type, scope); every positional annotation has a span inside the text; a layer keeps insertion order, is immutable once added, and cannot be added twice; a document-scoped layer has span-less values (language id, categories). DocumentAnalyzerTest covers the build-time checks and DocumentPipelineExampleTest the example in the manual.

Lineage. Standoff annotation as in the UIMA CAS, typed keys as in CoreNLP's annotation map, declared requires/provides as in spaCy's pipeline analysis, at library weight.

Docs: opennlp-docs/src/docbkx/document.xml. Has no dependency on other open PRs; the layer PRs (#1237, #1238) and the sandbox adapters build on it.

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krickert force-pushed the OPENNLP-1888-DocumentShape branch 3 times, most recently from 4cd9beb to 7e65aad Compare July 21, 2026 08:59
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krickert marked this pull request as ready for review July 21, 2026 09:07
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This was proposed about a week ago. Discussions pointed to this shape - I feel like it's a great direction as a lot of research went into landing this shape:

  • A single shared container for full pipelines: sentence, token, POS, lemma, and name annotations live in one Document with typed, offset-anchored layers instead of parallel arrays passed hand to hand.
  • Exact character-offset provenance: every annotation points back into the original text, the prerequisite for offset-aware normalization and span-level traceability.
  • A uniform DocumentAnnotator seam: new analysis steps (gazetteer joins, geocoding, quality scoring, PII detection, relation extraction) plug in as annotators over the same container rather than each inventing its own I/O shape.
  • Cross-component evidence sharing: one component's layer (for example emoji or entity annotations) is directly readable as features by another, with no glue code.
  • Cleaner downstream integration: document pipelines that use OpenNLP can consume one typed annotation record per document instead of adapting several tool-specific outputs.
  • Unblocks the staged follow-up branches that currently carry private copies of this container; once merged they rebase to plain, small diffs.

@rzo1

rzo1 commented Jul 21, 2026

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I think that this needs to wait a bit more until a few more people ump into the discussion: https://lists.apache.org/thread/jwxxjkc2b0dqn4rwjvt1t7cdf056gqhp

@krickert
krickert marked this pull request as draft July 21, 2026 10:14
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krickert force-pushed the OPENNLP-1888-DocumentShape branch from 7e65aad to b920e43 Compare July 24, 2026 03:21
krickert added a commit to ai-pipestream/opennlp that referenced this pull request Jul 24, 2026
…ENNLP-1895 recorded

Restate the map against apache main a864230, cut as 3.0.0-M5 on 2026-07-24.
apache#1177 (OPENNLP-1870) merged upstream and moves into the merged box, apache#1190 and
apache#1191 are marked ready for review, and OPENNLP-1895 (quantized embedding
tables) joins the diagram in its own colour: filed in JIRA with the pull
request deliberately held until apache#1165 and apache#1152 move.

Statuses now carry the measured GitHub draft flag and how far each head sits
behind main, which surfaces three things the old text did not: apache#1182 is a draft
again, apache#1167 is based on main rather than on apache#1155 and carries the seam and
isBlank commits as copies, and apache#1152 reports conflicts only because its
apache-hosted sentencepiece base has diverged from the refreshed head.
@krickert
krickert force-pushed the OPENNLP-1888-DocumentShape branch from b920e43 to 3ab6920 Compare July 24, 2026 19:27
krickert added a commit to ai-pipestream/opennlp that referenced this pull request Jul 24, 2026
…est head

All nine open heads now sit directly on a864230 and report mergeable. Two
were reporting conflicts and both cleared: apache#1167 through a plain rebase, and
apache#1152 by pointing its apache-hosted sentencepiece base branch at the refreshed
head it had drifted away from, which shrinks its diff back to the 30 commits it
owns. apache#1166 shed the 13 OPENNLP-1883 commits it carried, since apache#1163 is
upstream as a single squash, and is 3 commits now.

Also correct what the draft flag on apache#1182 means: the branch is review-ready and
waits on the upstream queue, not on unfinished work.
@rzo1

rzo1 commented Jul 28, 2026

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Review of PR #1182OPENNLP-1888: Document annotation container with typed offset-anchored layers

Blocking

opennlp-api/.../document/NameFinderAnnotator.java:136 — zero-length mention escapes the bounds check.
if (mention.getStart() < 0 || mention.getEnd() > count) does not reject getEnd() == 0. Span permits start == end (the contract test asserts zero-length spans are legal), so a finder returning new Span(0, 0) reaches line 141: tokens.get(first + mention.getEnd() - 1) indexes first - 1. For the first sentence that is IndexOutOfBoundsException; for a later sentence it silently takes the end offset of the previous sentence's last token and then new Span(start, end) throws IllegalArgumentException("start index must not be larger than end index"). Neither is the documented loud rejection. Add || mention.getStart() >= mention.getEnd() to the check and pin it with a test, next to testMentionOutsideSentenceTokensFailsLoud.

opennlp-api/.../document/Document.java:23-49 — interface Javadoc describes the implementation and threading.
"Documents are immutable: with(...) returns a new document that shares the unchanged layers. That immutability makes instances safe to share between threads." That is ImmutableDocument behaviour, not the interface contract, and threading belongs in the accepted phrasing "Thread safety is implementation specific." — which DocumentAnnotator:346 already uses correctly. Move the copy-on-add and sharing narrative to ImmutableDocument, keep the invariants (insertion order, once-only add, unmodifiable lists) on the interface where they are genuinely contractual.

ImmutableDocument.java:50 — the text is a CharSequence held by reference, so the immutability claim is not enforced.
empty(CharSequence) stores the caller's instance. Pass a StringBuilder and the document's text, the span bounds validated in with(...), and the "safe to share between threads" claim all become false after the caller mutates it. Either normalize to String on construction, or drop the immutability and thread-safety guarantees from the Javadoc. This is a new public type frozen at release, so it needs deciding now.

Three copies of the sentence/token walk loop.
NameFinderAnnotator.java:117, POSTaggerAnnotator.java:94, LemmatizerAnnotator.java:115 each contain the same ~25 lines: the while advancing next over tokens enclosed by the sentence span, the count == 0 continue, the per-sentence String[] fill, and the trailing token at ... lies outside every sentence check. Extract one helper. LemmatizerAnnotator lives in opennlp.tools.lemmatizer, so a package-private helper is not enough — either a public helper type in opennlp.tools.document or an abstract per-sentence annotator base.

MISSING_LAYER duplicated three times and inlined once.
Declared identically in NameFinderAnnotator.java:36, POSTaggerAnnotator.java:41, LemmatizerAnnotator.java:52, then spelled as a bare literal in StemmerAnnotator.java:81. Partial alignment is worse than none. One shared constant, or better one shared requireLayer(document, key) helper that throws, used by all four.

LemmatizerAnnotator.java:152,157 and StemmerAnnotator.java:93,98 — no Javadoc on requires()/provides().
The opennlp-api adapters put {@inheritDoc} on both. Same convention, or drop it from all six adapters.

DocumentPipelineExampleTest.java:172 — the example contradicts the documented contract and the manual.
TokenLengthAnnotator.annotate throws "document lacks the required layer " when the token layer is empty. The class Javadoc, DocumentAnnotator:355, and document.xml:205 all state that a required layer must be present but may be empty. The same class printed in the manual (document.xml:168) has no such check. This test is the reference example a first-time user copies, so it must not teach the opposite of the contract. Remove the tokens.isEmpty() branch.

Minor

  • LemmatizerAnnotator.java:95,99,103document.layers() called three times, each allocating a fresh unmodifiableSet wrapper. NameFinderAnnotator:99 and POSTaggerAnnotator:83 hoist it into a local; do the same here.
  • document.xml:76 and the other four listings — <![CDATA[ sits on its own line indented four tabs. Every existing chapter (stemmer.xml:40, :60) puts it on the <programlisting language="java"> line. The deviation also renders a leading blank line in each snippet.
  • DocumentAnalyzerTest.java:55,75,107,112 — fully qualified java.util.List, java.util.ArrayList, opennlp.tools.util.Sequence although java.util.List is imported at the top and the sibling test files import Sequence.
  • DocumentAnalyzerTest.java:168for (final String text : new String[] {"", " "}) is a hard-coded input array; make it a @ParameterizedTest so a failure names the offending input.
  • Test fixture duplication: SPLITTER/WHITESPACE in DocumentAnalyzerTest.java:43,66 are the same period splitter and whitespace tokenizer as PERIOD_SPLITTER/SPACE_TOKENIZER in DocumentPipelineExampleTest.java:60,87. Extract to a shared test utility.
  • DocumentAnalyzerTest.java:96"barks.".contains(sentence[i]) has the arguments reversed, so any substring of "barks." gets VBZ. It happens to pass; use a set lookup.
  • SentenceDetectorAnnotator, TokenizerAnnotator, POSTaggerAnnotator, NameFinderAnnotator, LemmatizerAnnotator, StemmerAnnotator are non-final public class while DocumentAnalyzer is final. Decide extensibility per class before the types freeze.
  • Layers.java:130 — the private constructor comment says "This class holds constants only and is never instantiated", but the class also exposes key(...) and documentKey(...). Fix the comment.
  • LemmatizerAnnotatorTest and StemmerAnnotatorTest use Assertions.assertEquals(...) throughout while the opennlp-api tests use static imports. Align.
  • NameFinderAnnotator.java:143 — the entity type is written both into the Span type and into the annotation value. Two sources of truth for the same fact; pick one and say which in the Javadoc.
  • StringUtil.java:283 — Javadoc says the argument "Must not be null" but there is no validation and no @throws. It matches the neighbouring isEmpty, so consistency is fine, but document the NPE.

Process

You have eight other open PRs (#1191, #1190, #1167, #1166, #1165, #1155, #1154, #1152). The duplication, {@inheritDoc} on overrides, repeated string literals as constants, interface-Javadoc-without-threading, and @ParameterizedTest for hard-coded input arrays are recurring items — please apply them to all open PRs likewise. No model-affecting changes here, so no eval build needed. Keeping this one draft until the four follow-ups land is right.

@krickert

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Thanks for taking the time I will address all of these within a few hours

@krickert
krickert force-pushed the OPENNLP-1888-DocumentShape branch from 819070c to 5ba76d6 Compare July 28, 2026 15:15
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All of it is addressed. The branch is rebased on current main.

Blocking

Zero-length mention. mention.getStart() >= mention.getEnd() added to the bounds check. Pinned by testZeroLengthMentionFailsLoud, which returns Span(0, 0) for the second sentence, the case that was mapped silently wrong rather than throwing, and asserts the adaptive data is still cleared.

Interface Javadoc. The copy-on-add and sharing narrative moved to ImmutableDocument. Document keeps only what is contractual (insertion order, once-only add, unmodifiable lists) and now says "Thread safety is implementation specific."

CharSequence held by reference. Normalized to String at construction, so the span bounds validated on insertion stay valid for the document's lifetime. testTextIsCapturedAtConstruction mutates a StringBuilder after construction and asserts the document is unchanged.

Three copies of the walk, and MISSING_LAYER. Both replaced by one public helper, opennlp.tools.document.DocumentAnnotators, since LemmatizerAnnotator sits in another package. It carries requireLayers(Document, LayerKey...) and forEachSentence(sentences, tokens, consumer). All four annotators use it, so the four spellings of the missing-layer rejection are now one, and DocumentAnnotatorsTest pins the helper as public API in its own right, including the walk's contiguous-run slicing and the token-outside-every-sentence rejection.

{@inheritDoc} on the runtime adapters. Added to requires() and provides() on both.

The example contradicting the contract. The tokens.isEmpty() branch is gone. TokenLengthAnnotator now calls DocumentAnnotators.requireLayers, which is the same rejection the contract describes, and the manual listing matches the test again.

Minor

Done: hoisted document.layers(); <![CDATA[ moved onto the programlisting line in all five listings; fully qualified names replaced with imports; @ParameterizedTest for the blank-input matrix; shared TestComponents for the period splitter and space tokenizer; Layers constructor comment corrected; static assertion imports in the two runtime tests; @throws NullPointerException documented on StringUtil.isBlank.

Reversed contains. Replaced with a Set.of("barks.", "eats.") lookup rather than left passing by accident.

Entity type in two places. The annotation value is now the single source. Spans are constructed untyped and the Javadoc says so, on both Layers.ENTITIES and the annotator. Tests assert span().getType() is null.

Extensibility. All six adapters are final, matching DocumentAnalyzer. Easier to open one later than to close one after the types freeze.

Since then a second pass folded the three copies of the "Ana runs. Bob sits." fixture in NameFinderAnnotatorTest into one helper, hoisted the no-op finder to a constant, and added a test pinning the exact null-document rejection across all four api-side adapters, which had no coverage.

The document package runs 65 tests, none skipped.

@krickert
krickert marked this pull request as ready for review July 28, 2026 22:43
@krickert
krickert requested review from jzonthemtn, mawiesne and rzo1 July 31, 2026 10:35
krickert added 11 commits August 5, 2026 22:10
…yers over the original text

Adds opennlp.tools.document to opennlp-api: Document (immutable, copy-on-add layer
container over the original text), Annotation (a typed value on a Span), LayerKey
(open, typed layer identity), and DocumentAnnotator (pipeline step declaring the
layers it requires and provides). DocumentAnalyzer assembles annotators into a
pipeline validated at build time. Standard keys in Layers cover sentences, tokens,
part-of-speech tags, and entities, populated through thin adapters over the existing
SentenceDetector, Tokenizer, POSTagger, and TokenNameFinder interfaces, which stay
the primary API for single-task use and are unchanged.

All spans refer to the text as supplied. No new dependencies.
…rom missing layers, validate providers at build time
… adaptive data on failure

The lemmatizer adapter now slices tokens and tags per sentence like its POS and
name-finder siblings, so lemmatization decisions never cross a sentence boundary,
and it declares the sentence layer as required. The POS adapter rejects a tagger
that returns a wrong tag count. The name-finder adapter rejects mentions whose
token indices lie outside their sentence instead of silently reading the next
sentence's tokens, clears adaptive data even when annotation fails, and derives
UNTYPED from NameSample.DEFAULT_TYPE instead of re-declaring the literal.
… definition

A blank check under the toolkit's whitespace definition, which unlike
String.isBlank covers the no-break spaces, so annotators validating labels and
identifiers share one predicate instead of each carrying a private copy. Reads
whole code points; tests pin the no-break and figure spaces, the empty string,
and a supplementary-plane letter.
…nt rule

Adds the Document Annotation Container chapter to the manual, with every code
example and every stated span and value mirroring the passing pipeline example
test. The review pass aligns the branch with the project's conventions: layer
key ids validate through StringUtil.isBlank, the annotator interface leaves
thread safety implementation specific, the sentence and tokenizer adapters
document annotate like their siblings, repeated rejection-message literals
become per-class constants, and the name finder test's nine anonymous fixtures
fold into one helper. Layers now states the key placement rule: core layer
keys live there, capability layer keys on their providing annotator.
Every key the toolkit defines now carries the opennlp: id prefix
(opennlp:sentences, opennlp:tokens, opennlp:pos, opennlp:entities,
opennlp:lemmas, opennlp:stems). An extension defines its keys under its own
prefix, and a bare id stays legal for an application-local layer, so ids from
independent producers cannot collide. The rule is stated on Layers, LayerKey,
and in the manual chapter.
A layer key now declares whether its layer is positional or document-scoped.
A positional key, the default, guarantees a span on every annotation, so
consumers never null-check one. A document-scoped key, created through
LayerKey.document, carries whole-document values without spans, the home for
a language id, a category distribution, or provenance. The scope is declared
per key, never per annotation: the container rejects a span-less annotation
under a positional key and a spanned annotation under a document-scoped key,
naming the layer either way. Scope participates in key equality.
…on text

The three invariants the contract tests already enforce are now stated on the
Document interface and in the manual chapter: layers preserve insertion order
and are never reordered, layers are immutable once added and detached from
the caller's input list, and adding a layer is once-only with the rejection
naming the key. Together they keep index-based references between layers
valid for the lifetime of the document.
A corpus may carry a hand-annotated version of a layer beside a produced one.
The convention is a gold: id prefix on the same key scheme, for example
gold:opennlp:tokens beside opennlp:tokens. Because adding a layer is
once-only, competing versions of a layer always live under distinct keys and
never replace each other. Stated on Layers and in the manual chapter, with a
contract test pinning the coexistence.
The chapter said offsets count characters; the pinned contract test
shows a supplementary-plane character counts as two. Say Java chars
(UTF-16 units) so the claim matches the tested behavior.
Three tests fail red: the adapters inherit the identity toString, so a
pipeline validation message reads 'annotator
opennlp.tools.document.SentenceDetectorAnnotator@3b96c42e requires
layer ...' instead of naming the adapter. The stemmer test pins the
full analyzer message exactly, since that adapter requires a single
layer and the message is therefore deterministic.
All six adapters override toString with the simple class name, so a
pipeline validation message names the offending annotator readably.
The pinned tests pass; opennlp-api and opennlp-runtime suites green.
@mawiesne

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@krickert Generally, this PR adds a lot of value as discussed / designed over the past months. What's the current state of it in terms of @rzo1's feedback comments? Are the latest doc-related changes reflected? Can I start my human review on it and have it consistently processed?

@mawiesne mawiesne added java Pull requests that update Java code tests Pull requests that add or update test code labels Aug 25, 2026
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@krickert Generally, this PR adds a lot of value as discussed / designed over the past months. What's the current state of it in terms of @rzo1's feedback comments? Are the latest doc-related changes reflected? Can I start my human review on it and have it consistently processed?

Yeah - I have jumped on this one many times over. I hope it's ready! I'll do one manual look right now but if it's green at least at some point I thought it was ready.

rzo1's suggestions helped a ton. It works well with other standards so I feel it's librarian-friendly. I feel like it's really a flexible design - I have about 20 branches based off of it.

Not gonna lie - to me it's the most important of tickets I have now. This in 3.0 would allow for almost all the features to confidently "drip" at whatever pace we want in the review process and not require a 4.0 release. It also unlocks most of the ability to deliver a sandbox version of the gRPC server since this shape is repeated in grpc.

So please do! I spent awhile thinking about this shape so the team's feedback is super important to me.

The shape is working exceptionally well with my features so far - I've tested it on about 3 sample apps - a custom BM25 search engine, a pipeline decoration step, and the opennlp grpc server. It's also similar to shapes I've seen in python counterparts.

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@mawiesne give me one sec - I'm doing a full check again - I am sure I addressed the comments but I didn't reply to all of them yet. I think it's good though if you want to start.

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@mawiesne the code concerns were addressed but I have to give a bunch of replies :) But I made the changes and think they look good.

@mawiesne

mawiesne commented Aug 26, 2026

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@krickert Had a first structural look on the additions. I've noticed an inconsistency, I'd like to get sorted before reading / thinking deeper:

I wonder why the SentenceDetectorAnnotator, TokenizerAnnotator, POSTaggerAnnotator and NameFinderAnnotator exist in opennlp-api? Those implement concrete class behavior and should therefore be moved to opennlp-runtime. LemmatizerAnnotator and StemmerAnnotator already live there.
It would be more consistent if all (concrete) *Annotator classes would land in the runtime jar. The API jar shall declare the contract and the actual impl can add annotators per desired NLP task.

Same applies for the *Annotator-related tests classes, oc. These are clearly something for the checks of impl classes in the core runtime. In general, we should aim for a very lightweight API jar.

Wdyt? FYI: @rzo1 @jzonthemtn

Note:

  1. I could even imagine another SpellCheckAnnotator in the spellcheck extension. But this is, oc, strictly component bound, thus the annotator class lives next to the component's classes.

@rzo1

rzo1 commented Aug 26, 2026

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@krickert Had a first structural look on the additions. I've noticed an inconsistency, I'd like to get sorted before reading / thinking deeper:

I wonder why the SentenceDetectorAnnotator, TokenizerAnnotator, POSTaggerAnnotator and NameFinderAnnotator exist in opennlp-api? Those implement concrete class behavior and should therefore be moved to opennlp-runtime. LemmatizerAnnotator and StemmerAnnotator already live there. It would be more consistent if all (concrete) *Annotator classes would land in the runtime jar. The API jar shall declare the contract and the actual impl can add annotators per desired NLP task.

Same applies for the *Annotator-related tests classes, oc. These are clearly something for the checks of impl classes in the core runtime. In general, we should aim for a very lightweight API jar.

Wdy? FYI: @rzo1 @jzonthemtn

Note:

  1. I could even imagine another SpellCheckAnnotator in the spellcheck extension. But this is, oc, strictly component bound, thus the annotator class lives next to the component's classes.

Agree.

+1 to the SpellCheckAnnotator proposal ;-)

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@mawiesne thank you for the suggestions - and agree with all of them. I'd never push back on any suggestion to make an API jar lighter. I've been working on it for a couple hours - almost done. I'll let you know when I push it.

krickert added a commit that referenced this pull request Aug 26, 2026
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Ready for your review:

I implemented both parts of your suggestion: the four concrete annotators and their tests now live in opennlp-runtime, and the annotators are placed with their respective components under sentdetect, tokenize, postag, and namefind. I also moved the API-only custom-layer contract test back to opennlp-api and removed a weaker duplicate runtime test.

Ready for any other suggestions. I like how it looks a lot more now.

krickert added a commit that referenced this pull request Aug 30, 2026
# Conflicts:
#	opennlp-api/src/main/java/opennlp/tools/util/StringUtil.java
#	opennlp-docs/src/docbkx/opennlp.xml
#	opennlp-tools/src/test/java/opennlp/tools/util/StringUtilTest.java
Adapts a Chunker to the document pipeline: reads sentences, tokens, and POS
tags and provides opennlp:chunks, one annotation per phrase chunk carrying its
type on the span of its tokens.
Adapts a constituency Parser to the document pipeline: reads sentences and
tokens and provides opennlp:phrases, one annotation per phrase node above the
part-of-speech level in pre-order, carrying the label and the span of the head
token the parser's head rules select.
Also makes the ParserAnnotator helpers instance methods, matching the other
adapters.
krickert added a commit that referenced this pull request Aug 30, 2026
…e container

The manual chapter opens with why the container exists next to the task
APIs, adds a table of the layers the toolkit's adapters provide with their
value types and span anchors, names the tests that pin each rule, and
states which established designs the shape follows.

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Thx @krickert for the PR!

@mawiesne
mawiesne merged commit d6b8641 into main Sep 1, 2026
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@mawiesne
mawiesne deleted the OPENNLP-1888-DocumentShape branch September 1, 2026 04:43
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