Triple
T15600480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Road House |
E375015
|
entity |
| Predicate | mainOccupationOfProtagonist |
P93070
|
FINISHED |
| Object | bouncer |
—
|
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: bouncer | Statement: [Road House, mainOccupationOfProtagonist, bouncer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainOccupationOfProtagonist Context triple: [Road House, mainOccupationOfProtagonist, bouncer]
-
A.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
mainOccupationFrom
chosen
Indicates that the specified occupation is the primary or main job held by the given entity.
-
D.
protagonistSocialStatus
Indicates the social standing or class position held by the story’s main character in relation to others in their society.
-
E.
proposerOccupation
Indicates the occupation or professional role held by the entity acting as the proposer in a given context.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e621fc4819097e8e85e7ddfdc6c |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:12 a.m.