Triple
T22587149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen F. Austin Lumberjacks and Ladyjacks |
E564827
|
entity |
| Predicate | sponsorGender |
P790
|
FINISHED |
| Object | men's sports |
—
|
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 sports | Statement: [Stephen F. Austin Lumberjacks and Ladyjacks, sponsorGender, men's sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorGender Context triple: [Stephen F. Austin Lumberjacks and Ladyjacks, sponsorGender, men's sports]
-
A.
sponsoredGender
Indicates that one entity provides financial or material sponsorship specifically related to the gender of another entity.
-
B.
genderOfMascot
Indicates the gender associated with a particular mascot.
-
C.
sponsorSport
chosen
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
-
D.
winnerGender
Indicates the gender of the entity that is the winner in a given event or competition.
-
E.
sportGender
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1615de7d48190b1ca46c76a1e609c |
completed | April 29, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:46 p.m.