Triple
T24720382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الراغب الأصفهاني |
E612276
|
entity |
| Predicate | أثر_علمي |
P157035
|
FINISHED |
| Object | اعتمد عليه كثير من المفسرين واللغويين بعده |
—
|
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: اعتمد عليه كثير من المفسرين واللغويين بعده | Statement: [الراغب الأصفهاني, أثر_علمي, اعتمد عليه كثير من المفسرين واللغويين بعده]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: أثر_علمي Context triple: [الراغب الأصفهاني, أثر_علمي, اعتمد عليه كثير من المفسرين واللغويين بعده]
-
A.
أثر_علمي
chosen
Indicates a scientific impact or influence that one entity (such as a work, researcher, or discovery) has on another within the scientific or academic domain.
-
B.
isScientific
Indicates that something pertains to or is based on systematic scientific methods, principles, or knowledge.
-
C.
hasScientificInterestIn
Indicates that one entity holds a scientific curiosity, concern, or research focus directed toward another entity.
-
D.
hasScience
Indicates that an entity possesses, includes, or is associated with a particular scientific discipline, content, or attribute.
-
E.
appliesResearchTo
Indicates that an entity uses or implements research findings, methods, or insights in relation to another entity, context, or problem.
- 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_69e2d7d6e7a48190bb43b0d8bb1137a0 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:40 a.m.