Triple
T33842396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yidaki |
E867389
|
entity |
| Predicate | genderRestrictions |
P29781
|
FINISHED |
| Object | traditionally played by men in many communities |
—
|
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: traditionally played by men in many communities | Statement: [Yidaki, genderRestrictions, traditionally played by men in many communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderRestrictions Context triple: [Yidaki, genderRestrictions, traditionally played by men in many communities]
-
A.
genderRule
chosen
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
B.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
-
C.
genderSpecificity
Indicates whether the relationship or action applies specifically to a particular gender or is gender-neutral.
-
D.
genderCustom
Indicates that an entity has a user-specified or non-standard gender designation beyond predefined gender categories.
-
E.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
- 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_69f34992ad40819087760ed939bd2a7a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:47 a.m.