Triple
T13510877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bakhtiari tribe |
E321134
|
entity |
| Predicate | relatedGroup |
P37
|
FINISHED |
| Object | Kuhgiluyeh Lurs |
E546433
|
NE 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: Kuhgiluyeh Lurs | Statement: [Bakhtiari tribe, relatedGroup, Kuhgiluyeh Lurs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuhgiluyeh Lurs Context triple: [Bakhtiari tribe, relatedGroup, Kuhgiluyeh Lurs]
-
A.
Kuhgiluyeh Lurs
chosen
Kuhgiluyeh Lurs are a regional branch of the Lur ethnic group traditionally inhabiting the Kuhgiluyeh area of southwestern Iran, known for their distinct dialect and cultural practices.
-
B.
Azarbarzin
Azarbarzin is a character from Persian epic tradition, known primarily as the son of the legendary hero Esfandiyar.
-
C.
Mahneshan
Mahneshan is a small city in northwestern Iran known for its rural surroundings and location within Zanjan Province.
-
D.
Firuzkuh
Firuzkuh is a small city in Tehran Province, Iran, known for its mountainous landscape and cool climate.
-
E.
Kalaleh
Kalaleh is a city in northeastern Iran known as a local administrative and agricultural center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf86a6208190be8c18f7a0158f23 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75490291c8190b5985d8c90ef1af6 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:43 p.m.