Triple
T24405712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Slam Champion (WWE) |
E615303
|
entity |
| Predicate | hasFemaleVersion |
P78555
|
FINISHED |
| Object | WWE Women’s Grand Slam Champion |
—
|
NE NERFINISHED |
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: WWE Women’s Grand Slam Champion | Statement: [Grand Slam Champion (WWE), hasFemaleVersion, WWE Women’s Grand Slam Champion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFemaleVersion Context triple: [Grand Slam Champion (WWE), hasFemaleVersion, WWE Women’s Grand Slam Champion]
-
A.
hasFemaleEquivalent
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
B.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
-
C.
hasFemaleFormOf
chosen
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
-
D.
hasFemaleSpeaker
Indicates that the associated content, event, or communication is spoken or narrated by a female individual.
-
E.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
- 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_69e2d7e780bc81908049c779e697a7f6 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294de76848190bd2cf3c7add2dcf1 |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.