Triple
T25060926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinhas |
E627653
|
entity |
| Predicate | linkedBiblicalRole |
P27433
|
FINISHED |
| Object | priest in the Tabernacle |
—
|
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: priest in the Tabernacle | Statement: [Pinhas, linkedBiblicalRole, priest in the Tabernacle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedBiblicalRole Context triple: [Pinhas, linkedBiblicalRole, priest in the Tabernacle]
-
A.
biblicalFigureRole
chosen
Indicates the specific role, function, or office that a biblical figure holds within a biblical narrative or tradition.
-
B.
associatedBiblicalFigure
Indicates that one entity is linked or connected to a particular biblical figure, such as by reference, attribution, or traditional association.
-
C.
associatedReligionRole
Indicates that one entity holds a specific religious role, office, or function in relation to another entity.
-
D.
religiousTextRole
Indicates the specific role or function that a religious text has in relation to a person, group, practice, or tradition.
-
E.
associatedBiblicalBook
Indicates that one entity is linked or connected to a specific book of the Bible as its relevant or referenced scriptural source.
- 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_69e2ff2c45f48190afa28369f1df6786 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 18, 2026, 6:10 a.m.