Triple
T19813894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolhan region |
E476012
|
entity |
| Predicate | majorTown |
P316
|
FINISHED |
| Object | Chaibasa |
E318469
|
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: Chaibasa | Statement: [Kolhan region, majorTown, Chaibasa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chaibasa Context triple: [Kolhan region, majorTown, Chaibasa]
-
A.
Chaibasa
chosen
Chaibasa is a town in eastern India that serves as the administrative headquarters of West Singhbhum district in the state of Jharkhand.
-
B.
Nalgonda
Nalgonda is a town and district headquarters in the Indian state of Telangana, known for its proximity to major irrigation projects and its historical significance in the region.
-
C.
Sambalpur
Sambalpur is a historic city and former princely region in western Odisha, India, known for its cultural heritage, textile traditions, and role in 19th-century colonial-era political events.
-
D.
Warangal
Warangal is a historic city in southern India known for its Kakatiya-era forts, temples, and monuments, and is one of the major urban centers of the state of Telangana.
-
E.
Bilaspur
Bilaspur is a town in the Yamunanagar district of Haryana, India, known as a local commercial and administrative center for surrounding rural areas.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654f6495c81908e7eea359a60e40f |
completed | April 20, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07cccc33fc8190958cc5d5cb2feb79 |
completed | May 16, 2026, 1:47 a.m. |
Created at: April 10, 2026, 1:50 p.m.