Triple
T1715302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Sexes tennis match |
E37275
|
entity |
| Predicate | winnerGender |
P32267
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [Battle of the Sexes tennis match, winnerGender, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerGender Context triple: [Battle of the Sexes tennis match, winnerGender, female]
-
A.
awardCategoryGender
Indicates that an award category is designated for recipients of a specific gender.
-
B.
winnerFullName
Indicates the full personal name of the entity that is the winner in a given event or competition.
-
C.
winnerCountry
Indicates the country that achieved first place or victory in a given competition, event, or contest.
-
D.
sportGender
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
E.
winnerNickname
Indicates the nickname used to refer to the entity that has won a particular contest, event, or competition.
- F. None of above. chosen
Provenance (4 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab7521878c8190b9e7739b8c3fc705 |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61bd46d48190915500d75a9d8e94 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab752034348190a1cc20955ed24f6f |
completed | March 7, 2026, 12:45 a.m. |
Created at: March 4, 2026, 7:30 p.m.