Triple
T23677104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caporales |
E584907
|
entity |
| Predicate | hasGenderRoles |
P69451
|
FINISHED |
| Object | male dancers |
—
|
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: male dancers | Statement: [Caporales, hasGenderRoles, male dancers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderRoles Context triple: [Caporales, hasGenderRoles, male dancers]
-
A.
hasGenderRole
chosen
Indicates that an entity is associated with, or expected to perform, a particular socially defined gender-based role or set of behaviors.
-
B.
sexualRole
Indicates the specific sexual function, position, or behavioral role one entity assumes in a sexual interaction or relationship with another.
-
C.
hasGenderSystem
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
-
D.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
-
E.
hasGenderConvention
Indicates that there is an established or customary way of assigning or expressing gender within a given context, system, or culture.
- 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f4d4388190a0e439f4df7a0f23 |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:51 p.m.