Triple
T36387927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States women's national lacrosse team |
E896246
|
entity |
| Predicate | hasPlayerGenderCategory |
P111986
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [United States women's national lacrosse team, hasPlayerGenderCategory, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlayerGenderCategory Context triple: [United States women's national lacrosse team, hasPlayerGenderCategory, female]
-
A.
eligiblePlayersGender
chosen
Indicates that the relationship specifies which player genders are allowed or considered eligible in a given context.
-
B.
playableGender
Indicates that a particular gender is available as a selectable option for a player character.
-
C.
genderCategoryIncludes
Indicates that a given gender category encompasses or contains the specified gender identity or subgroup.
-
D.
hasGenderSystem
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
-
E.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
- 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_69f76e52e3108190becf70b090ae7bd6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
Created at: May 3, 2026, 4:10 p.m.