Triple
T216718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dispute Settlement Understanding |
E4120
|
entity |
| Predicate | hasArticleCount |
P443
|
FINISHED |
| Object | 27 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 27 | Statement: [Dispute Settlement Understanding, hasArticleCount, 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArticleCount Context triple: [Dispute Settlement Understanding, hasArticleCount, 27]
-
A.
articleCount
chosen
Indicates the number of articles associated with a given entity or context.
-
B.
containsArticle
Indicates that one entity includes or holds an article (such as a written piece, item, or document) as part of its contents.
-
C.
titleCount
Indicates the number of distinct titles associated with an entity within a given context.
-
D.
hasTotalNumber
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
-
E.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b52190481908f299d26122bafd2 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.