Triple
T17920692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abihu |
E448057
|
entity |
| Predicate | moralLessonAssociated |
P57332
|
FINISHED |
| Object | holiness of God in worship |
—
|
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: holiness of God in worship | Statement: [Abihu, moralLessonAssociated, holiness of God in worship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralLessonAssociated Context triple: [Abihu, moralLessonAssociated, holiness of God in worship]
-
A.
moralAssociation
Indicates a perceived ethical or moral connection between entities, such as one influencing or reflecting the moral character, values, or judgment of the other.
-
B.
hasMoralMessage
chosen
Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
-
C.
moralTheme
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
D.
moralOfMyth
Indicates the underlying lesson, ethical teaching, or message conveyed by a myth.
-
E.
moralImplication
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30a11748190be41361d108aee58 |
completed | April 19, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:20 a.m.