Triple
T24234944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abraham ben Moses di Boton |
E601848
|
entity |
| Predicate | scholarlyFocus |
P102810
|
FINISHED |
| Object | codification of Jewish law |
—
|
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: codification of Jewish law | Statement: [Abraham ben Moses di Boton, scholarlyFocus, codification of Jewish law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scholarlyFocus Context triple: [Abraham ben Moses di Boton, scholarlyFocus, codification of Jewish law]
-
A.
scholarlyMilieu
Indicates the intellectual or academic environment, context, or community within which a scholarly work, activity, or figure is situated.
-
B.
scholarlyEmphasis
chosen
Indicates a relationship where an entity focuses its academic attention, research, or analysis predominantly on a particular subject, theme, or area of study.
-
C.
scholarlyView
Indicates that one entity holds an academic or research-based interpretation, opinion, or theoretical stance about another entity.
-
D.
scholarlyWork
Indicates a relationship where an entity is a formal academic or research work produced, published, or recognized within a scholarly context.
-
E.
scholarlyUse
Indicates that something is used for academic, educational, or research-related purposes.
- 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_69e29538aafc8190a2386fdebbd1393b |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f28a9a4b708190851504c302778fd2 |
completed | April 29, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:02 a.m.