Triple
T14130300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawza of Najaf |
E340145
|
entity |
| Predicate | academicDegreeEquivalent |
P45183
|
FINISHED |
| Object | ijtihad qualification |
—
|
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: ijtihad qualification | Statement: [Hawza of Najaf, academicDegreeEquivalent, ijtihad qualification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicDegreeEquivalent Context triple: [Hawza of Najaf, academicDegreeEquivalent, ijtihad qualification]
-
A.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
-
C.
diplomaEquivalence
chosen
Indicates that one diploma or academic qualification is recognized as equivalent in value or status to another.
-
D.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
E.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de610aa434819096671c5aabb9134a |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:23 p.m.