Triple
T16279137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chick Hicks |
E395217
|
entity |
| Predicate | roleInCarsFranchise |
P38898
|
FINISHED |
| Object | recurring antagonist |
—
|
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: recurring antagonist | Statement: [Chick Hicks, roleInCarsFranchise, recurring antagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCarsFranchise Context triple: [Chick Hicks, roleInCarsFranchise, recurring antagonist]
-
A.
carCultureRole
Indicates the role or function an entity has within car culture, such as how it contributes to or is perceived in automotive-related communities, practices, or values.
-
B.
roleInFranchiseHistory
chosen
Indicates the specific function, position, or contribution an entity has within the historical development or timeline of a franchise.
-
C.
roleInTesla
Indicates that one entity holds or held a specific role, position, or function within the organization Tesla.
-
D.
roleInToyota
Indicates that one entity holds a specific role, position, or function within the organization Toyota.
-
E.
franchiseCharacter
Indicates a relationship where a character belongs to, appears in, or is part of a particular media franchise.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24610908c8190921e507dcb4d8250 |
completed | April 17, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.