Triple
T27093793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESPY Award for Best Female Athlete |
E686236
|
entity |
| Predicate | isGenderedCounterpartOf |
P1613
|
FINISHED |
| Object | ESPY Award for Best Male Athlete |
—
|
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: ESPY Award for Best Male Athlete | Statement: [ESPY Award for Best Female Athlete, isGenderedCounterpartOf, ESPY Award for Best Male Athlete]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGenderedCounterpartOf Context triple: [ESPY Award for Best Female Athlete, isGenderedCounterpartOf, ESPY Award for Best Male Athlete]
-
A.
femaleCounterpartOf
Indicates that one entity is the female equivalent or corresponding counterpart of another entity within a given role, relationship, or category.
-
B.
hasNeutralPronoun
Indicates that an entity is referred to using a gender-neutral pronoun.
-
C.
genderedFormOf
Indicates that one term is a gender-specific variant or inflected form corresponding to another, more neutral or differently gendered term.
-
D.
hasGenderInterpretation
Indicates that an entity is associated with a particular interpretation or understanding of gender.
-
E.
hasFemaleEquivalent
chosen
Indicates that one entity serves as the female counterpart or equivalent of another entity.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f623ad825c8190a1bdbf8aa76879b4 |
completed | May 2, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 8:42 a.m.