Triple
T28975962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bullet to the Head |
E734410
|
entity |
| Predicate | mainCoProtagonistOccupation |
P138179
|
FINISHED |
| Object | detective |
—
|
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: detective | Statement: [Bullet to the Head, mainCoProtagonistOccupation, detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCoProtagonistOccupation Context triple: [Bullet to the Head, mainCoProtagonistOccupation, detective]
-
A.
otherProtagonistOccupation
Indicates that another main character in the narrative has a specific occupation or job role.
-
B.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
C.
hasCoProtagonistOccupation
chosen
Indicates that two or more co-protagonists share a specified occupation or professional role.
-
D.
occupationAsPersona
Indicates that an entity holds or performs a particular occupation specifically in the role or persona of another characterized identity.
-
E.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
- 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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 28, 2026, 9:08 a.m.