Triple

T17202122
Position Surface form Disambiguated ID Type / Status
Subject Munda–Nicobarese branch E417500 entity
Predicate hasSubgroup P747 FINISHED
Object Munda languages NE NERFINISHED

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: Munda languages | Statement: [Munda–Nicobarese branch, hasSubgroup, Munda languages]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munda languages
Context triple: [Munda–Nicobarese branch, hasSubgroup, Munda languages]
  • A. Munda languages chosen
    Munda languages are a branch of the Austroasiatic language family spoken primarily by indigenous communities in eastern and central India.
  • B. Thura-Yura languages
    Thura-Yura languages are a group of closely related Australian Aboriginal languages traditionally spoken in parts of South Australia.
  • C. Muna–Buton languages
    The Muna–Buton languages are a subgroup of Austronesian languages spoken primarily in southeastern Sulawesi and nearby islands in Indonesia.
  • D. Moru–Madi languages
    The Moru–Madi languages are a subgroup of related Central Sudanic languages spoken primarily in South Sudan, Uganda, and the Democratic Republic of the Congo.
  • E. Tebu languages
    The Tebu languages are a group of closely related Saharan languages spoken primarily by the Tebu people across parts of Chad, Niger, and Libya.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42db014b08190b88a5001e9f7811b completed April 19, 2026, 1:19 a.m.
Created at: April 10, 2026, 5:38 a.m.