Triple
T19422073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations Charter Article 35 |
E485879
|
entity |
| Predicate | hasThreeParagraphs |
P69278
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [United Nations Charter Article 35, hasThreeParagraphs, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThreeParagraphs Context triple: [United Nations Charter Article 35, hasThreeParagraphs, true]
-
A.
hasTwoParagraphs
Indicates that the related content or text is composed of exactly two distinct paragraphs.
-
B.
hasNumberOfParagraphs
chosen
Indicates that an entity is associated with a specific count of paragraphs it contains or comprises.
-
C.
hasParagraph
Indicates that one entity contains or is associated with a specific paragraph as part of its content or structure.
-
D.
hasThreePartStructure
Indicates that something is organized into three distinct, related parts or sections.
-
E.
hasThreeBooksWith
Indicates that two entities are related by one having exactly three books together with the other (e.g., jointly owned, shared, or associated as a group of three books).
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e632159d7081909d004544ec5992c0 |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.