Triple

T1106529
Position Surface form Disambiguated ID Type / Status
Subject Lata Mangeshkar E25498 entity
Predicate languagesSungIn P11404 FINISHED
Object Odia E24420 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: Odia | Statement: [Lata Mangeshkar, languagesSungIn, Odia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odia
Context triple: [Lata Mangeshkar, languagesSungIn, Odia]
  • A. Odia chosen
    Odia is an Indo-Aryan language spoken primarily in the Indian state of Odisha, known for its rich literary tradition and classical language status.
  • B. Banga
    Banga is an Indian-origin surname most prominently associated with Ajay Banga, the business executive and current President of the World Bank.
  • C. Kurukh
    Kurukh is an indigenous Dravidian language spoken primarily by the Oraon tribal communities in eastern and central India.
  • D. Santhali
    Santhali is an Austroasiatic language spoken primarily by the Santal people in eastern India, Bangladesh, Nepal, and Bhutan.
  • E. Odishi
    Odishi is the historical name for a region in western Georgia, corresponding largely to present-day Samegrelo and known for its distinct Mingrelian culture and history.
  • 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_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bb75eec08190b1d6545e96816d34 completed March 1, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c4cee1881909ca8af01f22bb8bb completed March 7, 2026, 4:03 p.m.
Created at: March 1, 2026, 7:43 p.m.