Triple
T29757105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAFTA Award for Best Actress in a Supporting Role (for Nightcrawler) |
E753058
|
entity |
| Predicate | genderOfRole |
P163566
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [BAFTA Award for Best Actress in a Supporting Role (for Nightcrawler), genderOfRole, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderOfRole Context triple: [BAFTA Award for Best Actress in a Supporting Role (for Nightcrawler), genderOfRole, female]
-
A.
genderOfPersona
Indicates the gender identity associated with a given persona.
-
B.
hasGenderRole
Indicates that an entity is associated with, or expected to perform, a particular socially defined gender-based role or set of behaviors.
-
C.
sexualRole
Indicates the specific sexual function, position, or behavioral role one entity assumes in a sexual interaction or relationship with another.
-
D.
genderRoleAssociation
Indicates an association between a gender and a particular social role, behavior, or expectation.
-
E.
femaleRole
chosen
Indicates that the role, function, or position involved is associated with or designated as female.
- 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_69f0d62c84cc8190846f80ae04fdf8ec |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67f7efc3c8190986d2d95b7a23729 |
completed | May 2, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 28, 2026, 7:57 p.m.