Triple
T10081703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pishva County |
E213915
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Pishva |
E845228
|
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: Pishva | Statement: [Pishva County, hasCapital, Pishva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pishva Context triple: [Pishva County, hasCapital, Pishva]
-
A.
Pishva
chosen
Pishva is a city in Tehran Province, Iran, known as an administrative and local commercial center for the surrounding region.
-
B.
Sorkheh
Sorkheh is a small city in north-central Iran known for its location within Semnan Province and its semi-arid climate.
-
C.
Bijar
Bijar is a town in Iran renowned for producing exceptionally durable, densely knotted Persian carpets known for their rich colors and intricate designs.
-
D.
Oshnavieh
Oshnavieh is a small city in northwestern Iran known for its Kurdish population and mountainous surroundings near the border with Iraq.
-
E.
Zanjanrud
Zanjanrud is a river in northwestern Iran that flows through the city of Zanjan and its surrounding region.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd03482d481908b03d35dc2d16395 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3174109988190b703bb5b7c89c5c2 |
completed | April 6, 2026, 2:15 a.m. |
Created at: March 30, 2026, 9 p.m.