Triple
T23245551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mosaic Law |
E581573
|
entity |
| Predicate | containsApproximateNumberOfCommandments |
P2331
|
FINISHED |
| Object | 613 |
—
|
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: 613 | Statement: [Mosaic Law, containsApproximateNumberOfCommandments, 613]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsApproximateNumberOfCommandments Context triple: [Mosaic Law, containsApproximateNumberOfCommandments, 613]
-
A.
numberOfCommandments
chosen
Indicates the total count of commandments associated with a given subject.
-
B.
containsCommandment
Indicates that one entity includes or encompasses a specific commandment as part of its content or structure.
-
C.
commandmentHebrewName
Indicates the Hebrew-language name assigned to a particular commandment.
-
D.
commandmentType
Indicates the specific category or kind of commandment that an instruction or directive belongs to.
-
E.
commandmentSource
Indicates that one entity is the origin, authority, or issuing source from which a particular commandment or directive is derived.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f0f5d88190a497f14601f9bf29 |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:10 p.m.