Triple
T23023251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Over Her Dead Body |
E573225
|
entity |
| Predicate | mainMaleProtagonistOccupation |
P21567
|
FINISHED |
| Object | veterinarian |
—
|
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: veterinarian | Statement: [Over Her Dead Body, mainMaleProtagonistOccupation, veterinarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainMaleProtagonistOccupation Context triple: [Over Her Dead Body, mainMaleProtagonistOccupation, veterinarian]
-
A.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
B.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
C.
protagonistSocialStatus
Indicates the social standing or class position held by the story’s main character in relation to others in their society.
-
D.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
E.
protagonistDescription
Indicates that a text provides a descriptive summary or characterization of the story’s main protagonist.
- 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_69e245b821008190b0e09cb02092aae1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1847b86688190b678d0d09ecd3c3d |
completed | April 29, 2026, 4:09 a.m. |
| PD | Predicate disambiguation | batch_69ef3ba004a48190885aece88efd1f52 |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:52 p.m.