Triple
T25415806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Day of the Outlaw |
E636828
|
entity |
| Predicate | actorForCharacter Helen Crane |
P158827
|
FINISHED |
| Object | Tina Louise |
—
|
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: Tina Louise | Statement: [Day of the Outlaw, actorForCharacter Helen Crane, Tina Louise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actorForCharacter Helen Crane Context triple: [Day of the Outlaw, actorForCharacter Helen Crane, Tina Louise]
-
A.
actorForCharacter Jack Bruhn
Indicates that Jack Bruhn is the actor who portrays or performs the role of a particular character.
-
B.
mainActorForCharacter_CharlieCrews
Indicates that the referenced person is the primary actor who portrays the character Charlie Crews.
-
C.
hasHumanCharacterRole
Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
-
D.
actorForCharacterSheriffGilCorrigan
Indicates that an entity is the actor who portrays the character Sheriff Gil Corrigan.
-
E.
componentCharacter1
Indicates that one entity is the first (primary) character component or constituent part of another entity.
- 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_69e75db4135881909acc287ebcb7a505 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5b0119ee0819088c4985bd7862cab |
completed | May 2, 2026, 8:04 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 1:55 p.m.