Triple
T2683762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry Holmes vs. Gerry Cooney |
E57433
|
entity |
| Predicate | roundOfStoppage |
P41488
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Larry Holmes vs. Gerry Cooney, roundOfStoppage, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roundOfStoppage Context triple: [Larry Holmes vs. Gerry Cooney, roundOfStoppage, 13]
-
A.
hasStopNear
Indicates that one entity has a stop or stopping point located in close proximity to another entity.
-
B.
round
Indicates that an entity has a circular or approximately circular shape or form.
-
C.
hasStopArea
Indicates that an entity is associated with or contains a specific stop area, such as a designated location where vehicles stop.
-
D.
stoppedAt
Indicates that an entity has come to a halt or pause at a specific location or point in time.
-
E.
openedAsRailStop
Indicates that an entity began operation or was first established specifically as a railway stop.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9d7692c81909d8fd9ce3817161b |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81c9b4c81908e5e0da6ac5f828b |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd891bcd481909af5340a64ff69f9 |
completed | March 7, 2026, 7:49 a.m. |
Created at: March 6, 2026, 9:54 p.m.