Triple
T36264889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Una mujer fantástica |
E892193
|
entity |
| Predicate | leadActorIdentity |
P166850
|
FINISHED |
| Object | transgender woman |
—
|
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: transgender woman | Statement: [Una mujer fantástica, leadActorIdentity, transgender woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorIdentity Context triple: [Una mujer fantástica, leadActorIdentity, transgender woman]
-
A.
leadActorParent
Indicates that one entity is the parent of the lead actor associated with another entity (such as a film, show, or performance).
-
B.
leadActorOfAdaptation
Indicates that a person is the main actor in a specific adaptation of a work (such as a film, series, or stage version).
-
C.
leadRoleActor
chosen
Indicates that an actor performs a leading or principal role in a work or production.
-
D.
leadActorNicknameHolder
Indicates that the subject is the person who holds or uses the nickname associated with the lead actor.
-
E.
leadCharacterField
Indicates that one entity serves as the primary or main character associated with another entity, such as a work or production.
- 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.