Triple
T25713826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wind |
E644803
|
entity |
| Predicate | leadFemalePerformanceRecognizedAs |
P6108
|
FINISHED |
| Object | one of Lillian Gish’s finest roles |
—
|
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: one of Lillian Gish’s finest roles | Statement: [The Wind, leadFemalePerformanceRecognizedAs, one of Lillian Gish’s finest roles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadFemalePerformanceRecognizedAs Context triple: [The Wind, leadFemalePerformanceRecognizedAs, one of Lillian Gish’s finest roles]
-
A.
leadingActressNominee
Indicates that a person has been nominated for an award in the leading actress category for a particular work or performance.
-
B.
leadActress
chosen
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
C.
leadActorAwarded
Indicates that the person in the lead actor role has received an award for their performance.
-
D.
leadActorNominee
Indicates that an entity was nominated for a lead acting role in relation to a particular work or award.
-
E.
bestActressMotionPictureMusicalOrComedyWork
Indicates that a work received the Golden Globe award for Best Actress in a Motion Picture – Musical or Comedy.
- 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc6008a4819084116248372fdd78 |
completed | May 2, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 9:22 p.m.