Triple
T1168224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hick from French Lick |
E24848
|
entity |
| Predicate | appliedInSport |
P17882
|
FINISHED |
| Object | basketball |
—
|
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: basketball | Statement: [The Hick from French Lick, appliedInSport, basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedInSport Context triple: [The Hick from French Lick, appliedInSport, basketball]
-
A.
appliesToSports
Indicates that something is relevant, appropriate, or specifically intended for use in the context of sports.
-
B.
usedInSport
Indicates that something (such as an object, technique, or concept) is employed or utilized within the context of a particular sport.
-
C.
includesSport
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
D.
representsInSport
Indicates that one entity serves as an official representative of another entity within the context of a particular sport or sporting domain.
-
E.
sportsInvolvement
chosen
Indicates the nature or extent of an entity’s participation in, association with, or role within a sport or sporting activity.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bccef84481908864e819884af86c |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.