Triple
T4626505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In the Mix |
E101109
|
entity |
| Predicate | leadActorPlaysBodyguard |
P57513
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [In the Mix, leadActorPlaysBodyguard, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorPlaysBodyguard Context triple: [In the Mix, leadActorPlaysBodyguard, true]
-
A.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
B.
hasStuntDouble
Indicates that one entity serves as a stunt double who performs dangerous or physically demanding actions on behalf of another entity.
-
C.
policeCharacter
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
-
D.
leadActorPlaysVersionOfSelf
Indicates that the lead actor in a work portrays a character that is a version or representation of themselves.
-
E.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a0a7b588190bc6552ee5babb198 |
completed | March 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:13 p.m.