Triple
T36409213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Durand |
E896830
|
entity |
| Predicate | workedAsStuntPerformerIn |
P161943
|
FINISHED |
| Object | Halloween H20: 20 Years Later |
—
|
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: Halloween H20: 20 Years Later | Statement: [Chris Durand, workedAsStuntPerformerIn, Halloween H20: 20 Years Later]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workedAsStuntPerformerIn Context triple: [Chris Durand, workedAsStuntPerformerIn, Halloween H20: 20 Years Later]
-
A.
stuntPerformerIn
chosen
Indicates that one entity serves as a stunt performer in a work, production, or performance associated with another entity.
-
B.
actsIn
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
-
C.
hasStuntDouble
Indicates that one entity serves as a stunt double who performs dangerous or physically demanding actions on behalf of another entity.
-
D.
leadActorPerformedOwnStunts
Indicates that the lead actor personally carried out the stunts in the production rather than using a stunt double.
-
E.
partOfFilmographyOf
Indicates that a work (such as a film, show, or role) is included in the body of screen-related works credited to a particular person.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.