Triple
T11496768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Hashr |
E272553
|
entity |
| Predicate | containsDivineNamesSection |
P99807
|
FINISHED |
| Object | verses 22–24 |
—
|
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: verses 22–24 | Statement: [Al-Hashr, containsDivineNamesSection, verses 22–24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsDivineNamesSection Context triple: [Al-Hashr, containsDivineNamesSection, verses 22–24]
-
A.
containsDivineName
Indicates that the referenced entity includes or explicitly mentions a divine or sacred name within its content.
-
B.
divineSign
Indicates that one entity serves as a supernatural or sacred omen, message, or signal from a divine source to another entity.
-
C.
hasLiturgicalName
Indicates that an entity is associated with a specific name used in liturgical or religious worship contexts.
-
D.
hasDivineModel
Indicates that something is patterned after, based on, or derived from a divine or sacred archetype or example.
-
E.
hasDivisionNames
Indicates that an entity is associated with one or more names of its internal divisions or subunits.
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de183f08190abfa36eaabc61dc6 |
completed | April 10, 2026, 2:18 a.m. |
| PD | Predicate disambiguation | batch_69d808736c5c8190899b5b3b2e797f65 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822ef46988190a1c360da4ee14fef |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:36 p.m.