Triple
T18142763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulster Covenant |
E434302
|
entity |
| Predicate | womenSignatoriesCount |
P130612
|
FINISHED |
| Object | about 234,000 |
—
|
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: about 234,000 | Statement: [Ulster Covenant, womenSignatoriesCount, about 234,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenSignatoriesCount Context triple: [Ulster Covenant, womenSignatoriesCount, about 234,000]
-
A.
numberOfSignatories
Indicates the total count of entities that have formally signed or endorsed a given document, agreement, or item.
-
B.
foundingSignatory
Indicates that an entity was an original signer or member at the founding of another entity, agreement, or organization.
-
C.
wasSignatoryOf
Indicates that an entity formally signed or endorsed a specific document, agreement, or treaty as a participating party.
-
D.
hasSignatories
Indicates that one or more parties have formally signed or endorsed an agreement, document, or instrument.
-
E.
laterSignatoriesCount
Indicates the number of other entities that became signatories after the referenced entity.
- F. None of above. chosen
Provenance (4 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de0c8aa88190b4ded7e6d05f6edf |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:29 a.m.