Triple
T33860892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhattathiri |
E867918
|
entity |
| Predicate | traditionalOccupationAssociation |
P17109
|
FINISHED |
| Object | scholar |
—
|
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: scholar | Statement: [Bhattathiri, traditionalOccupationAssociation, scholar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalOccupationAssociation Context triple: [Bhattathiri, traditionalOccupationAssociation, scholar]
-
A.
traditionalOccupations
chosen
Indicates that an entity is associated with occupations or jobs that are customary, long-established, or culturally traditional within a particular community or context.
-
B.
occupationalAssociation
Indicates a relationship where one entity is connected to another through a job, profession, or work-related role.
-
C.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
D.
recognizedOccupationOf
Indicates that one entity is acknowledged or officially accepted as the occupation or professional role held by another entity.
-
E.
derivesFromOccupation
Indicates that one entity originates from, is obtained through, or is a result of another entity’s occupation or professional role.
- 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_69f349943ccc8190a3c41a3e0ae46cbf |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
Created at: May 1, 2026, 1:47 a.m.