Triple
T22047263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Nimar district |
E544793
|
entity |
| Predicate | administrativeHeadquarters |
P62
|
FINISHED |
| Object | Khargone |
—
|
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: Khargone | Statement: [West Nimar district, administrativeHeadquarters, Khargone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khargone Context triple: [West Nimar district, administrativeHeadquarters, Khargone]
-
A.
Khargone
chosen
Khargone is a city in western Madhya Pradesh, India, known as an agricultural and commercial center in the Nimar region.
-
B.
Limkheda
Limkheda is a town in the Dahod district of Gujarat, India, known as a local administrative and market center for surrounding rural areas.
-
C.
Khambhat
Khambhat is a historic coastal town in Gujarat, India, known for its ancient port, trade heritage, and distinctive gulf on the Arabian Sea.
-
D.
Jhabua
Jhabua is a town and administrative district headquarters in western Madhya Pradesh, India, known for its significant tribal population and culture.
-
E.
Chandkheda
Chandkheda is a residential and industrial locality in the northwestern part of Ahmedabad, Gujarat, known for its proximity to major infrastructure and educational institutions.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12830c674819080254d77ee02bc9f |
completed | April 28, 2026, 9:35 p.m. |
Created at: April 16, 2026, 8:26 p.m.