Triple
T28136106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Corn Is Green |
E714209
|
entity |
| Predicate | leadActorForCharacter Miss Moffat |
P1507
|
FINISHED |
| Object | Bette Davis |
—
|
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: Bette Davis | Statement: [The Corn Is Green, leadActorForCharacter Miss Moffat, Bette Davis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacter Miss Moffat Context triple: [The Corn Is Green, leadActorForCharacter Miss Moffat, Bette Davis]
-
A.
characterPlayedBy_MichelleRyan
Indicates that the subject is a character portrayed or played by Michelle Ryan.
-
B.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
C.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
D.
leadActorForCharacter Philip Shayne
Indicates that the specified person is the primary actor portraying the character Philip Shayne.
-
E.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
- 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_69efd6af156c81908f50c2cd7db0e1ef |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 9:50 p.m.