Triple
T428598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1936 Summer Olympics |
E9663
|
entity |
| Predicate | genderParticipation |
P7453
|
FINISHED |
| Object | men and women |
—
|
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 and women | Statement: [1936 Summer Olympics, genderParticipation, men and women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderParticipation Context triple: [1936 Summer Olympics, genderParticipation, men and women]
-
A.
sportGender
chosen
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
B.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
-
C.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
D.
numberOfFemaleAthletes
Indicates the count of athletes who are female in a given context or group.
-
E.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eeecb64c81908c5c83ef7c0181e6 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd7a3608190b8785c7b7205f6c1 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.