Triple
T26611298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AP Athlete of the Year (male) |
E667928
|
entity |
| Predicate | isGenderSpecificVersionOf |
P48671
|
FINISHED |
| Object | AP Athlete of the Year |
—
|
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: AP Athlete of the Year | Statement: [AP Athlete of the Year (male), isGenderSpecificVersionOf, AP Athlete of the Year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGenderSpecificVersionOf Context triple: [AP Athlete of the Year (male), isGenderSpecificVersionOf, AP Athlete of the Year]
-
A.
hasGenderVariant
chosen
Indicates that one entity is a gender-specific form or variant of another entity.
-
B.
isUnisexVariantOf
Indicates that one item is a gender-neutral or unisex version or form of another item.
-
C.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
D.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
E.
isVersionOf
Indicates that one entity is a particular version, edition, or variant derived from 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_69ee9cfe16088190a3dddd68e3c7b1ea |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f615a93e3c8190a569c4d548da9900 |
completed | May 2, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 2:16 a.m.