Triple
T29367516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anjra |
E744759
|
entity |
| Predicate | hasNotableFieldOfRenown |
P39276
|
FINISHED |
| Object | Islamic scholarship |
—
|
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: Islamic scholarship | Statement: [Anjra, hasNotableFieldOfRenown, Islamic scholarship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFieldOfRenown Context triple: [Anjra, hasNotableFieldOfRenown, Islamic scholarship]
-
A.
hasNotableRecognitionFor
Indicates that an entity has received notable recognition, such as awards, honors, or distinctions, specifically for another entity or achievement.
-
B.
hasMannerOfNotoriety
Indicates that an entity is known or recognized in a particular way, specifying the manner or type of its notoriety.
-
C.
hasNotableRecognitionAs
Indicates that an entity has received notable recognition, distinction, or status specifically in the role, capacity, or identity denoted by the related entity.
-
D.
hasNotablePeople
Indicates that certain people associated with an entity are distinguished or noteworthy in some recognized way.
-
E.
notableField
chosen
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
- 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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69ffac35ac5481908b6bdfd5bbe8c76e |
completed | May 9, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69ffabbfd2548190964c851496bbbaee |
completed | May 9, 2026, 9:48 p.m. |
Created at: April 28, 2026, 2:24 p.m.