Triple
T7730475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koya |
E175235
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Odisha |
E76751
|
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: Odisha | Statement: [Koya, spokenIn, Odisha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Odisha Context triple: [Koya, spokenIn, Odisha]
-
A.
Orissa
chosen
Orissa is a historical region and modern Indian state on the eastern coast of India, known for its rich cultural heritage, ancient temples, and significant role in the subcontinent’s political and economic history.
-
B.
Chhattisgarh
Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
-
C.
Jharkhand
Jharkhand is an eastern Indian state known for its rich mineral resources, significant tribal population, and extensive forests and plateaus.
-
D.
West Bengal
West Bengal is an eastern Indian state known for its cultural heritage, literature, and the metropolis of Kolkata (formerly Calcutta).
-
E.
Andhra Pradesh
Andhra Pradesh is a state in southeastern India known for its long coastline along the Bay of Bengal, Telugu-speaking population, and major cities such as Visakhapatnam and Vijayawada.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703358cf881909df8496d943d6de7 |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c922ac9c108190a9f00381d951b20d |
completed | March 29, 2026, 1:01 p.m. |
Created at: March 27, 2026, 4:06 p.m.