Triple
T1715303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Sexes tennis match |
E37275
|
entity |
| Predicate | loserGender |
P32268
|
FINISHED |
| Object | male |
—
|
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: male | Statement: [Battle of the Sexes tennis match, loserGender, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loserGender Context triple: [Battle of the Sexes tennis match, loserGender, male]
-
A.
loserParty
Indicates that a particular political party was the one that lost in a given election or contest.
-
B.
loserStatus
Indicates that an entity has been judged or designated as the loser in a particular comparison, contest, or evaluative context.
-
C.
loserScore
Indicates the number of points or score achieved by the losing participant in a competitive event or comparison.
-
D.
loserPoints
Indicates the number of points awarded to or accumulated by the losing side in a competitive event or comparison.
-
E.
lost
Indicates that an entity no longer possesses or has been deprived of another entity it previously had.
- 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.