Triple
T20676664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Beach Games |
E508175
|
entity |
| Predicate | includesGenderCategories |
P2577
|
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: [Asian Beach Games, includesGenderCategories, men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesGenderCategories Context triple: [Asian Beach Games, includesGenderCategories, men]
-
A.
genderCategories
chosen
Indicates the classification of an entity into one or more gender-related categories or identities.
-
B.
overseesGenderCategory
Indicates that one entity has responsibility for supervising, managing, or administering a particular gender category associated with another entity.
-
C.
includesBothGenders
Indicates that the referenced group, set, or category contains members of both male and female genders.
-
D.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
E.
sponsoredGender
Indicates that one entity provides financial or material sponsorship specifically related to the gender of another entity.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6bea24f288190928f828e5f567257 |
completed | April 21, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:44 a.m.