Triple
T31306822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mullá Ḥusayn |
E798353
|
entity |
| Predicate | religiousTraditionOfOrigin |
P140779
|
FINISHED |
| Object | Twelver Shia Islam |
—
|
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: Twelver Shia Islam | Statement: [Mullá Ḥusayn, religiousTraditionOfOrigin, Twelver Shia Islam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousTraditionOfOrigin Context triple: [Mullá Ḥusayn, religiousTraditionOfOrigin, Twelver Shia Islam]
-
A.
partOfReligiousTradition
Indicates that one entity belongs to, is included within, or is practiced as a component of a particular religious tradition.
-
B.
religiousTraditionDetail
chosen
Indicates the specific religious tradition, denomination, or doctrinal detail associated with an entity or relationship.
-
C.
previousReligiousTradition
Indicates that an entity had a different or prior religious affiliation or tradition before its current one.
-
D.
religionAtOrigin
Indicates that an entity had a particular religion or religious affiliation at the time or place of its origin.
-
E.
religiousTraditions
Indicates a relationship where certain religious customs, practices, or belief systems are associated with or observed by an entity.
- 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_69f224e0bd4c8190aab9b29a73f7aa3c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: April 29, 2026, 9:14 p.m.