Triple
T8329443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Every Which Way but Loose |
E195037
|
entity |
| Predicate | ClintEastwoodRole |
P82129
|
FINISHED |
| Object | Clint Eastwood plays Philo Beddoe |
—
|
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: Clint Eastwood plays Philo Beddoe | Statement: [Every Which Way but Loose, ClintEastwoodRole, Clint Eastwood plays Philo Beddoe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ClintEastwoodRole Context triple: [Every Which Way but Loose, ClintEastwoodRole, Clint Eastwood plays Philo Beddoe]
-
A.
leadActorAlsoDirector
Indicates that the person who plays the lead acting role in a production is also the director of that same production.
-
B.
workedAsDirectorFor
Indicates that one entity held the role of director in relation to another entity, such as an organization, project, or production.
-
C.
directorSince
Indicates that one entity has held the role of director for another entity starting from a specified point in time.
-
D.
filmDirectorOfAssociatedWork
Indicates that a person serves as the director of the specified creative work (such as a film or related audiovisual production).
-
E.
roleOfAndrewDavis
Indicates that an entity holds the role or position associated with Andrew Davis in relation to 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fb812508190aed8a283dacf712e |
completed | March 31, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:56 p.m.