Triple
T26098790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Wajiz fi Fiqh al-Imam al-Shafi'i |
E658344
|
entity |
| Predicate | authorKnownAs |
P154536
|
FINISHED |
| Object | al-Ghazali |
—
|
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-Ghazali | Statement: [al-Wajiz fi Fiqh al-Imam al-Shafi'i, authorKnownAs, al-Ghazali]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorKnownAs Context triple: [al-Wajiz fi Fiqh al-Imam al-Shafi'i, authorKnownAs, al-Ghazali]
-
A.
authorIsKnownFor
Indicates that a particular author is widely recognized or notable for a specific work, genre, contribution, or characteristic.
-
B.
alsoKnownAsRealAuthor
chosen
Indicates that an entity is an alternative or alias name identifying the same individual who is the actual (real) author of a work.
-
C.
workByAuthorAlsoKnownFor
Indicates that a work is created by an author who is also notably recognized for another specified work or contribution.
-
D.
hasAuthorAlsoKnownFor
Indicates that the author of a work is additionally recognized or notable for another specific work, role, or achievement.
-
E.
authorOfNamesFor
Indicates that one entity is the creator or originator of the names assigned to another entity or set of entities.
- 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_69ee5bc09c288190bc42a11972841383 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 26, 2026, 7:53 p.m.