Triple
T25666169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sky Blue Soccer |
E643521
|
entity |
| Predicate | clubOwnedGenderCategory |
P73600
|
FINISHED |
| Object | women’s |
—
|
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: women’s | Statement: [Sky Blue Soccer, clubOwnedGenderCategory, women’s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clubOwnedGenderCategory Context triple: [Sky Blue Soccer, clubOwnedGenderCategory, women’s]
-
A.
hasGenderedTeams
Indicates that the entity organizes or participates in teams that are separated or defined based on gender.
-
B.
hasGenderedTeam
Indicates that a team is organized or classified according to the gender of its members.
-
C.
parentClubGender
chosen
Indicates the gender category (e.g., men’s, women’s, mixed) associated with the parent club in a club–team or club–division relationship.
-
D.
genderOfMascot
Indicates the gender associated with a particular mascot.
-
E.
eligiblePlayersGender
Indicates that the relationship specifies which player genders are allowed or considered eligible in a given 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_69e77e7e45648190a068ed3faa8016ea |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fb2e5e548190a0b3a84b02c07940 |
completed | May 2, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 7:04 p.m.