Triple
T34599574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shimon Baadani |
E888420
|
entity |
| Predicate | religiousLawSpecialization |
P200226
|
FINISHED |
| Object | Sephardic 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: Sephardic halakha | Statement: [Shimon Baadani, religiousLawSpecialization, Sephardic halakha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousLawSpecialization Context triple: [Shimon Baadani, religiousLawSpecialization, Sephardic halakha]
-
A.
religiousLawAspect
Indicates that one entity represents a specific aspect, dimension, or component of a religious law associated with another entity.
-
B.
religiousLawView
Indicates a person's stance, interpretation, or opinion regarding a particular religious law or set of religious legal principles.
-
C.
religiousJurisdiction
Indicates that one entity holds official religious authority or governance over another entity or area.
-
D.
canonLawSpecialization
Indicates a professional or academic focus specifically on canon law as an area of expertise or study.
-
E.
halakhicFunction
Indicates a relationship where something serves a role, purpose, or effect within the framework of Jewish law (halakha).
- F. None of above. chosen
Provenance (4 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_69f349d489d48190ba30e7d97c6f5ef9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff7bc112088190851501fb2a16103d |
completed | May 9, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69ff7b45507c81909753866ad733601a |
completed | May 9, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69ff7bbfa4b08190b11e84861706b349 |
completed | May 9, 2026, 6:23 p.m. |
Created at: May 1, 2026, 2:03 a.m.