Triple
T30619271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tall T |
E779400
|
entity |
| Predicate | leadActorForCharacter Pat Brennan |
P180054
|
FINISHED |
| Object | Randolph Scott |
—
|
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: Randolph Scott | Statement: [The Tall T, leadActorForCharacter Pat Brennan, Randolph Scott]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacter Pat Brennan Context triple: [The Tall T, leadActorForCharacter Pat Brennan, Randolph Scott]
-
A.
leadActorForCharacterGaryBrannon
Indicates that a person is the primary actor portraying the character Gary Brannon in a production.
-
B.
leadActorForCharacter Philip Shayne
Indicates that the specified person is the primary actor portraying the character Philip Shayne.
-
C.
leadActorForCharacter David Greene
Indicates that the specified person is the primary actor portraying the character David Greene.
-
D.
leadActorForCharacter_MaceBrown
Indicates that a person is the primary actor portraying the character Mace Brown.
-
E.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
- F. None of above. chosen
Provenance (4 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_69f224a3307081909a6dca8ca75dbf48 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 29, 2026, 8:26 p.m.