Triple
T2655286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmet Catch |
E54592
|
entity |
| Predicate | jerseyNumberOfTyree |
P2651
|
FINISHED |
| Object | 85 |
—
|
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: 85 | Statement: [Helmet Catch, jerseyNumberOfTyree, 85]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyNumberOfTyree Context triple: [Helmet Catch, jerseyNumberOfTyree, 85]
-
A.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
C.
leaderJerseyColor
Indicates the color of the jersey worn by the current leader in a competition or ranking.
-
D.
reasonForJerseyNumber
Indicates the explanation or motivation behind an entity’s choice of a particular jersey number.
-
E.
jersey
Indicates that one entity is the jersey (sports uniform top) associated with, worn by, or representing another entity.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.