Triple
T29683632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elementary |
E751022
|
entity |
| Predicate | coLeadCharacterOccupation |
P158712
|
FINISHED |
| Object | sober companion |
—
|
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: sober companion | Statement: [Elementary, coLeadCharacterOccupation, sober companion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coLeadCharacterOccupation Context triple: [Elementary, coLeadCharacterOccupation, sober companion]
-
A.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
B.
otherProtagonistOccupation
chosen
Indicates that another main character in the narrative has a specific occupation or job role.
-
C.
leadActorOccupation
Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
-
D.
leadCharacterSecondaryOccupation
Indicates that the lead character has a secondary or additional occupation beyond their primary role.
-
E.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
- 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_69f0d625b09481909b0b69aea1e846c8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f6728d8d8881909cc97dd523866934 |
completed | May 2, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 7:12 p.m.