Triple
T21389473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Dworkin |
E527601
|
entity |
| Predicate | roleInScreamResurrection |
P144036
|
FINISHED |
| Object | co-developer |
—
|
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: co-developer | Statement: [Dan Dworkin, roleInScreamResurrection, co-developer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInScreamResurrection Context triple: [Dan Dworkin, roleInScreamResurrection, co-developer]
-
A.
roleInDeadByDaylight
Indicates the specific function or character type an entity has within the context of the game Dead by Daylight.
-
B.
roleInResidentEvilApocalypse
Indicates that an entity portrays a specific role or character in the film "Resident Evil: Apocalypse."
-
C.
roleInDeaths
Indicates the role or involvement an entity had in causing, contributing to, or being responsible for one or more deaths.
-
D.
roleInTheNightmareBeforeChristmas
Indicates the specific role or character that an entity has in the movie "The Nightmare Before Christmas."
-
E.
roleInDisasterMovie
Indicates that an entity has a specific acting or production role in a disaster-themed movie.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0f8ae288190b43df9fe2841a822 |
completed | April 22, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e61b3e47f881908fb2aac9bd2bfb58 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 16, 2026, 5:13 p.m.