Triple
T23395337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berar region |
E559341
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Akola |
—
|
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: Akola | Statement: [Berar region, majorCity, Akola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akola Context triple: [Berar region, majorCity, Akola]
-
A.
Akola
chosen
Akola is a major city in the Vidarbha region of Maharashtra, India, known as an important commercial and educational center.
-
B.
Alirajpur
Alirajpur is a town and district headquarters in western Madhya Pradesh, India, known for its predominantly tribal population and vibrant indigenous culture.
-
C.
Bhopalgarh
Bhopalgarh is a town in the Indian state of Rajasthan, known for its rural setting and administrative role within the region.
-
D.
Ashoknagar
Ashoknagar is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its agricultural economy and regional trade.
-
E.
Talcher
Talcher is an industrial town in Odisha, India, known for its coalfields and power plants within the Angul district.
- 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4db1c888190ace5d58bcc8645c1 |
completed | April 29, 2026, 6:27 a.m. |
Created at: April 17, 2026, 5:36 p.m.