Triple
T1424735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Jacobs |
E30303
|
entity |
| Predicate | sportsDisciplineInvolved |
P17882
|
FINISHED |
| Object | ice hockey |
—
|
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: ice hockey | Statement: [Jeremy Jacobs, sportsDisciplineInvolved, ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsDisciplineInvolved Context triple: [Jeremy Jacobs, sportsDisciplineInvolved, ice hockey]
-
A.
sportsInvolvement
chosen
Indicates the nature or extent of an entity’s participation in, association with, or role within a sport or sporting activity.
-
B.
sportEventType
Indicates the specific kind or category of sport associated with a given sporting event.
-
C.
includesSport
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
D.
sportNumber
Indicates the specific jersey or uniform number associated with an athlete in a sporting context.
-
E.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.