Triple
T11696387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasdeo River |
E278005
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Korba district |
E211365
|
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: Korba district | Statement: [Hasdeo River, flowsThrough, Korba district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korba district Context triple: [Hasdeo River, flowsThrough, Korba district]
-
A.
Korba
Korba is a coastal town in northeastern Tunisia known for its beaches, agriculture, and role as a local commercial center.
-
B.
Korba
chosen
Korba is an industrial city in the Indian state of Chhattisgarh, known primarily for its coal mining and power generation industries.
-
C.
Dantewada district
Dantewada district is a mineral-rich, predominantly tribal district in the southern part of Chhattisgarh, India, known for both its dense forests and its history of Maoist insurgency.
-
D.
Sidhi district
Sidhi district is an administrative district in the Indian state of Madhya Pradesh, known for its coal mining areas and part of the Singrauli region.
-
E.
Kalahandi district
Kalahandi district is an administrative region in the Indian state of Odisha, known for its tribal population, cultural diversity, and historical association with poverty and drought.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47cef60819088b7cc3a3a711e4c |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1471cba88190a7abdcbf4f579ea9 |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.