Triple
T30905026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | بدر الدين العيني |
E787275
|
entity |
| Predicate | المدرسة_الفقهية |
P160945
|
FINISHED |
| Object | المدرسة الحنفية في مصر المملوكية |
—
|
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: المدرسة الحنفية في مصر المملوكية | Statement: [بدر الدين العيني, المدرسة_الفقهية, المدرسة الحنفية في مصر المملوكية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: المدرسة_الفقهية Context triple: [بدر الدين العيني, المدرسة_الفقهية, المدرسة الحنفية في مصر المملوكية]
-
A.
الانتماء الفقهي
chosen
Indicates the doctrinal or jurisprudential school to which an entity is affiliated or adheres.
-
B.
madhhab
Indicates the school of thought or legal tradition within a broader religious or jurisprudential system that an entity follows or is associated with.
-
C.
schoolOf
Indicates that an educational institution is the one where a person studied, worked, or is otherwise academically affiliated.
-
D.
fiqh
Indicates the relationship of deriving, applying, or adhering to Islamic legal rulings and jurisprudential judgments regarding actions or situations.
-
E.
fiqhScope
Indicates the domain or scope within Islamic jurisprudence (fiqh) to which a particular ruling, issue, or concept applies.
- 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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6927dd38081909f32b60565283795 |
completed | May 3, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:50 p.m.