Triple
T27471622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Revenge (1976 film) |
E693334
|
entity |
| Predicate | leadActorForCharacterVurrla |
P9616
|
FINISHED |
| Object | Stockard Channing |
—
|
NE NERFINISHED |
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: Stockard Channing | Statement: [Sweet Revenge (1976 film), leadActorForCharacterVurrla, Stockard Channing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacterVurrla Context triple: [Sweet Revenge (1976 film), leadActorForCharacterVurrla, Stockard Channing]
-
A.
featuresVillainActor
Indicates that the subject includes or presents an actor in the role of a villain.
-
B.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
-
C.
leadActorAlsoVoices
Indicates that the lead actor in a production also provides the voice for a character, typically in an animated or voice-over role.
-
D.
playedBy
chosen
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
E.
leadCharacterCaste
Indicates that the lead character in a work belongs to a specified caste.
- 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_69ef538105548190a771cc5a0cf8c211 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 12:54 p.m.