Triple
T2956573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Kentucky Hilltoppers |
E79943
|
entity |
| Predicate | genderInclusive |
P36340
|
FINISHED |
| Object | men's teams |
—
|
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: men's teams | Statement: [Western Kentucky Hilltoppers, genderInclusive, men's teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderInclusive Context triple: [Western Kentucky Hilltoppers, genderInclusive, men's teams]
-
A.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
-
B.
hasNeutralPronoun
Indicates that an entity is referred to using a gender-neutral pronoun.
-
C.
usesGenderAccurateLanguage
Indicates that the language employed in the context correctly reflects and respects the gender identities of the entities referenced.
-
D.
genderInclusiveProgram
chosen
Indicates that a program is designed and implemented to be inclusive and respectful of all genders, avoiding bias or exclusion based on gender identity or expression.
-
E.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992998f08190ac9428310983172e |
completed | March 8, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69ad960c5c8881909d679912bd7d78f3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:57 p.m.