Triple
T24297808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adidas OCEAUNZ |
E606011
|
entity |
| Predicate | designedForGenderCompetition |
P7453
|
FINISHED |
| Object | women’s football |
—
|
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 football | Statement: [Adidas OCEAUNZ, designedForGenderCompetition, women’s football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedForGenderCompetition Context triple: [Adidas OCEAUNZ, designedForGenderCompetition, women’s football]
-
A.
designedForCompetition
Indicates that something was intentionally created or configured to be used in a competitive context or event.
-
B.
hasFemaleCompetitors
Indicates that an entity participates in a competitive context where at least some of the competitors are female.
-
C.
sportGender
chosen
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
D.
genreOfCompetition
Indicates the specific type or category of competition that an event or contest belongs to.
-
E.
winnerGender
Indicates the gender of the entity that is the winner in a given event or competition.
- 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_69e29549335881909cbf27adcaba1cf0 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f2915ada688190aa9c4bdaa2f1617f |
completed | April 29, 2026, 11:16 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 12:09 a.m.