Triple
T6106635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan Golf Tour |
E136132
|
entity |
| Predicate | primaryGender |
P46670
|
FINISHED |
| Object | men |
—
|
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 | Statement: [Japan Golf Tour, primaryGender, men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryGender Context triple: [Japan Golf Tour, primaryGender, men]
-
A.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
B.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
C.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
D.
featuredGender
chosen
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
-
E.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
- 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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b806bd48190b6f020af3391adb8 |
completed | March 22, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c049f80e2081909b7d84a104cda68d |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.