Triple
T15802795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bashan |
E383136
|
entity |
| Predicate | knownInBiblicalPoetryFor |
P120133
|
FINISHED |
| Object | fat cattle |
—
|
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: fat cattle | Statement: [Bashan, knownInBiblicalPoetryFor, fat cattle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownInBiblicalPoetryFor Context triple: [Bashan, knownInBiblicalPoetryFor, fat cattle]
-
A.
hasPoeticEpigraphs
Indicates that one entity (typically a work) includes poetic epigraphs associated with or prefacing another entity.
-
B.
isOftenRecitedFor
Indicates that something (such as a text, phrase, or piece of music) is frequently spoken, chanted, or performed for a particular purpose, audience, or occasion.
-
C.
associatedBiblicalFigure
Indicates that one entity is linked or connected to a particular biblical figure, such as by reference, attribution, or traditional association.
-
D.
usedByPoet
Indicates that something (such as a word, style, device, or object) is employed or utilized by a poet.
-
E.
subsectionOfTanakh
Indicates that one text division is a recognized subsection within the larger structure of the Tanakh.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b523bf508190af4a54bdc983a9a1 |
completed | April 16, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e00e48d49c819081afccb02f9cf18b |
completed | April 15, 2026, 10:16 p.m. |
Created at: April 10, 2026, 4:48 a.m.