Triple
T37404628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shmuel HaNavi neighborhood |
E929088
|
entity |
| Predicate | religiousLawObserved |
P99376
|
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: [Shmuel HaNavi neighborhood, religiousLawObserved, Halakha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousLawObserved Context triple: [Shmuel HaNavi neighborhood, religiousLawObserved, Halakha]
-
A.
religiousLawView
Indicates a person's stance, interpretation, or opinion regarding a particular religious law or set of religious legal principles.
-
B.
religiousLawAspect
chosen
Indicates that one entity represents a specific aspect, dimension, or component of a religious law associated with another entity.
-
C.
observanceDependsOnLaw
Indicates that the performance or fulfillment of an observance is contingent upon, or determined by, a particular law or legal requirement.
-
D.
religiousLawSpecialization
Indicates a relationship where an entity’s area of legal expertise is specifically focused on religious law.
-
E.
religiousJurisdiction
Indicates that one entity holds official religious authority or governance over another entity or area.
- 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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a002249ee388190a9501ee7630dc658 |
completed | May 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_6a002189273881909b6b687e2d61f5b1 |
completed | May 10, 2026, 6:11 a.m. |
Created at: May 3, 2026, 4:16 p.m.