Triple
T2652095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bnei Mikra |
E53922
|
entity |
| Predicate | identityFocus |
P31647
|
FINISHED |
| Object | direct interpretation of Scripture |
—
|
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: direct interpretation of Scripture | Statement: [Bnei Mikra, identityFocus, direct interpretation of Scripture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: identityFocus Context triple: [Bnei Mikra, identityFocus, direct interpretation of Scripture]
-
A.
focusType
chosen
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
subjectIdentity
Indicates that two or more references correspond to the same underlying entity or individual identity.
-
D.
formerFocus
Indicates that an entity previously served as the primary focus or main subject of attention, but no longer holds that status.
-
E.
identifierFor
Indicates that one entity serves as a unique identifying label or code for another entity.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.