Triple

T8879221
Position Surface form Disambiguated ID Type / Status
Subject Korba E211365 entity
Predicate abbreviation P43 FINISHED
Object Korba 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 | Statement: [Korba, abbreviation, Korba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korba
Context triple: [Korba, abbreviation, Korba]
  • A. Korba chosen
    Korba is an industrial city in the Indian state of Chhattisgarh, known primarily for its coal mining and power generation industries.
  • B. Korba
    Korba is a coastal town in northeastern Tunisia known for its beaches, agriculture, and role as a local commercial center.
  • C. Raigarh
    Raigarh is a regional dialect of the Chhattisgarhi language spoken in and around the Raigarh area of the Indian state of Chhattisgarh.
  • D. Narsinghpur
    Narsinghpur is a city and administrative center in central India known for its agricultural economy, particularly sugarcane and pulses, within the state of Madhya Pradesh.
  • E. Contai
    Contai is a coastal town in eastern India known as a regional commercial and transport hub in the Purba Medinipur district of West Bengal.
  • 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_69ca838e78748190934d82db3104f855 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc614ad1908190a77808fcf7f3e531 completed April 1, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba1809dc81909776f1268cae9004 completed April 3, 2026, 1:01 p.m.
Created at: March 30, 2026, 6:52 p.m.