Triple
T7004593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asher ben Jehiel |
E162420
|
entity |
| Predicate | primaryFieldOfWork |
P63305
|
FINISHED |
| Object | Halakha |
—
|
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: Halakha | Statement: [Asher ben Jehiel, primaryFieldOfWork, Halakha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryFieldOfWork Context triple: [Asher ben Jehiel, primaryFieldOfWork, Halakha]
-
A.
primaryWork
Indicates that one work is the main or most significant work associated with a given entity, as opposed to other secondary or related works.
-
B.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
C.
primaryField
chosen
Indicates the main area of focus, discipline, or domain most centrally associated with an entity.
-
D.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
-
E.
primaryArea
Indicates that one entity is the main or most important area, domain, or field associated with another entity.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc14037c81908bb87250ef29be50 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.