Triple
T22827292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishapur |
E565694
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Kazerun |
—
|
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: Kazerun | Statement: [Bishapur, locatedNear, Kazerun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kazerun Context triple: [Bishapur, locatedNear, Kazerun]
-
A.
Kazerun
chosen
Kazerun is a historic city in southwestern Iran known for its proximity to the ancient ruins of Bishapur and its cultural significance within Fars Province.
-
B.
Ardestan
Ardestan is an ancient city in central Iran known for its historic architecture, including notable mosques and traditional urban fabric.
-
C.
Shahrud
Shahrud is a major city in northeastern Iran known as an important regional hub for transportation, agriculture, and access to nearby natural attractions such as the Alborz Mountains and desert landscapes.
-
D.
Bavanat
Bavanat is a small city in southern Iran known for its traditional rural landscapes, gardens, and location within the mountainous region of Fars Province.
-
E.
Andimeshk
Andimeshk is a city in southwestern Iran known as a regional transportation hub and gateway to the Zagros Mountains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2914188190be6cdbd8167cd806 |
completed | April 29, 2026, 3:42 a.m. |
Created at: April 17, 2026, 3:34 p.m.