Triple
T7471152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hajj al-Qiran |
E176506
|
entity |
| Predicate | legalSchoolDiscussion |
P72858
|
FINISHED |
| Object | discussed in Sunni fiqh |
—
|
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: discussed in Sunni fiqh | Statement: [Hajj al-Qiran, legalSchoolDiscussion, discussed in Sunni fiqh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalSchoolDiscussion Context triple: [Hajj al-Qiran, legalSchoolDiscussion, discussed in Sunni fiqh]
-
A.
legalSchoolContrastedWith
Indicates a contrast or opposition drawn between two legal schools, highlighting their differing principles, methods, or doctrines.
-
B.
legalSchoolPractice
chosen
Indicates that a particular legal practice, method, or approach is characteristic of, endorsed by, or derived from a specific school or tradition of law.
-
C.
lawSchoolName
Indicates the name of the law school with which an entity (such as a person or institution) is associated.
-
D.
lawSchoolAccreditation
Indicates that a law school has been formally evaluated and recognized as meeting established educational and professional standards by an accrediting authority.
-
E.
lawSchoolRankingContext
Indicates the contextual ranking information associated with a law school, such as its position or status within a specified ranking system or timeframe.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f4145d608190bd93239f04f7da41 |
completed | March 27, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:41 p.m.