Triple

T7306417
Position Surface form Disambiguated ID Type / Status
Subject Munda E167985 entity
Predicate language P15 FINISHED
Object Mundari language E201634 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: Mundari language | Statement: [Munda, language, Mundari language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mundari language
Context triple: [Munda, language, Mundari language]
  • A. Mundari chosen
    Mundari is an Austroasiatic Munda language of eastern India, spoken primarily by the Munda people in states such as Jharkhand, Odisha, and West Bengal.
  • B. Munduruku language
    The Munduruku language is an indigenous Tupian language spoken by the Munduruku people of the Amazon region in Brazil.
  • C. Mandar language
    Mandar is an Austronesian language spoken primarily by the Mandar people along the western coast of Sulawesi in Indonesia.
  • D. Murle language
    The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
  • E. Mandeali language
    Mandeali language is an Indo-Aryan language spoken primarily in the Mandi region of Himachal Pradesh, India.
  • 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_69c6888d8e3c81909db79714903baf31 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6ebd7dcf88190b3e66bea327fc63d completed March 27, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e5603a288190a19d426905781cae completed March 28, 2026, 2:27 p.m.
Created at: March 27, 2026, 3:01 p.m.