Triple
T24656898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ʿAbd al-Karim al-Qushayri |
E610416
|
entity |
| Predicate | hasNisba |
P84454
|
FINISHED |
| Object | al-Qushayri |
—
|
NE NERFINISHED |
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: al-Qushayri | Statement: [ʿAbd al-Karim al-Qushayri, hasNisba, al-Qushayri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNisba Context triple: [ʿAbd al-Karim al-Qushayri, hasNisba, al-Qushayri]
-
A.
usesNisba
Indicates that one entity forms or applies a nisba (a relational or adjectival form, often derived from a name or place) to or in relation to another entity.
-
B.
usedNisba
chosen
Indicates that one entity is described or classified using a nisba (relational adjective or gentilic) derived from another entity.
-
C.
hasNoun
Indicates that an entity possesses or is associated with a specific noun as an attribute, label, or grammatical component.
-
D.
hasLadinName
Indicates that an entity is associated with a specific name expressed in the Ladin language.
-
E.
hasNameInArabic
Indicates that an entity is associated with a specific name expressed in the Arabic language.
- 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_69e2c4d453248190a020354e93ef6282 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:34 a.m.