Triple
T32900117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Psycho |
E841584
|
entity |
| Predicate | protagonistEmployerLocation |
P180563
|
FINISHED |
| Object | Wall Street |
—
|
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: Wall Street | Statement: [American Psycho, protagonistEmployerLocation, Wall Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistEmployerLocation Context triple: [American Psycho, protagonistEmployerLocation, Wall Street]
-
A.
protagonistLocation
Indicates the location or setting where the story’s main protagonist is situated at a given time.
-
B.
employerInPlot
Indicates that one entity serves as the employer of another within the context of a specific plot or storyline.
-
C.
mainCharacterWorkplaceType
Indicates the type or kind of workplace where the main character is employed or primarily works.
-
D.
protagonistParentOccupation
Indicates the occupation or job held by the protagonist’s parent in the described context.
-
E.
protagonistEmployerFamilyName
Indicates the family name (surname) of the employer of the story’s protagonist.
- 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: May 1, 2026, 1:19 a.m.