Triple
T6173689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leviticus 23 |
E137764
|
entity |
| Predicate | includesInstruction |
P69226
|
FINISHED |
| Object | grain offerings |
—
|
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: grain offerings | Statement: [Leviticus 23, includesInstruction, grain offerings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesInstruction Context triple: [Leviticus 23, includesInstruction, grain offerings]
-
A.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
B.
curriculumIncluded
Indicates that a particular subject, topic, or component is part of a defined curriculum or course of study.
-
C.
reasoningIncludes
Indicates that a reasoning process or argument explicitly incorporates or makes use of the referenced element as one of its components or steps.
-
D.
issueIncludes
Indicates that an issue or problem encompasses, contains, or involves a specified element, component, or sub-issue as part of its scope.
-
E.
includesSee
Indicates that one entity’s scope, content, or experience contains or encompasses the act of seeing or visual perception involving another entity.
- 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_69c008a68c508190a8d78245c865960e |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d94c47481909745b2533926a1ca |
completed | March 22, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69c055f7f12881908e21c04e9b752ba4 |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c056df95ac8190bc5efe050d3af864 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:18 p.m.