Triple
T23484044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buffs |
E570480
|
entity |
| Predicate | secondarySportAssociation |
P17808
|
FINISHED |
| Object | men’s 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: men’s basketball | Statement: [Buffs, secondarySportAssociation, men’s basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondarySportAssociation Context triple: [Buffs, secondarySportAssociation, men’s basketball]
-
A.
secondarySport
chosen
Indicates that an entity participates in or is associated with a sport that is not their primary or main sport.
-
B.
primarySports
Indicates that a particular sport is the main or most important sport associated with an entity (such as a person, team, or organization).
-
C.
sportsAssociation
Indicates a formal relationship in which an entity is affiliated with, governed by, or participates under the auspices of a specific sports organization or governing body.
-
D.
relatedSport
Indicates that there is an association or connection between an entity and a particular sport.
-
E.
countrySportAssociation
Indicates a relationship where a country is associated with, participates in, or is represented in a particular 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_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a752c678819087e5c50b8cf87d3d |
completed | April 29, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:03 p.m.