Triple
T36879726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Trail Drive |
E911442
|
entity |
| Predicate | featuresActorRoleType |
P204181
|
FINISHED |
| Object | Ken Maynard as cowboy lead |
—
|
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: Ken Maynard as cowboy lead | Statement: [The Trail Drive, featuresActorRoleType, Ken Maynard as cowboy lead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresActorRoleType Context triple: [The Trail Drive, featuresActorRoleType, Ken Maynard as cowboy lead]
-
A.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
B.
featuresCastMemberRole
chosen
Indicates that a work includes a specific role performed by a cast member.
-
C.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
D.
featuresActorInMultipleRoles
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
E.
featuresCastType
Indicates that one entity includes or highlights a particular type or category of cast (e.g., actors or performers) associated with it.
- 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_69f76e82339881909607a65c0503d941 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.