Triple
T19591847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shabbat Shekalim |
E470254
|
entity |
| Predicate | commandmentSource |
P136382
|
FINISHED |
| Object | Torah commandment of machatzit ha-shekel |
—
|
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: Torah commandment of machatzit ha-shekel | Statement: [Shabbat Shekalim, commandmentSource, Torah commandment of machatzit ha-shekel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commandmentSource Context triple: [Shabbat Shekalim, commandmentSource, Torah commandment of machatzit ha-shekel]
-
A.
commandmentType
Indicates the specific category or kind of commandment that an instruction or directive belongs to.
-
B.
commandmentHebrewName
Indicates the Hebrew-language name assigned to a particular commandment.
-
C.
containsCommandment
Indicates that one entity includes or encompasses a specific commandment as part of its content or structure.
-
D.
numberOfCommandments
Indicates the total count of commandments associated with a given subject.
-
E.
scripturalSourceType
Indicates the type or category of source from which a scriptural text or reference is derived.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6405646f0819089436d5517c03047 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
| PDg | Predicate description generation | batch_69e5174b060c81908937ff9ff7fce611 |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 1:43 p.m.