Triple
T26364665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ondel-ondel |
E660299
|
entity |
| Predicate | genderPairing |
P51833
|
FINISHED |
| Object | male and female couple |
—
|
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 and female couple | Statement: [Ondel-ondel, genderPairing, male and female couple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderPairing Context triple: [Ondel-ondel, genderPairing, male and female couple]
-
A.
genderRoleAssociation
Indicates an association between a gender and a particular social role, behavior, or expectation.
-
B.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
C.
genderConfiguration
chosen
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
D.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
-
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_69ee8126d52c8190bc0b34337c2c9aa8 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6102b07fc81908c14c1bcca28c1b0 |
completed | May 2, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 10:54 p.m.