Triple

T14786449
Position Surface form Disambiguated ID Type / Status
Subject Anuak language E347537 entity
Predicate neighboringLanguages P16383 FINISHED
Object Majang language E247384 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: Majang language | Statement: [Anuak language, neighboringLanguages, Majang language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Majang language
Context triple: [Anuak language, neighboringLanguages, Majang language]
  • A. Majang language chosen
    The Majang language is a Surmic language of the Nilo-Saharan family spoken by the Majangir people of southwestern Ethiopia.
  • B. Magahi language
    Magahi language is an Eastern Indo-Aryan language spoken primarily in the Indian state of Bihar and surrounding regions, closely related to languages like Bhojpuri and Maithili.
  • C. Mangseng language
    The Mangseng language is an Oceanic language spoken in Papua New Guinea, belonging to the Western Bismarck subgroup of the Austronesian language family.
  • D. Mangayat language
    The Mangayat language is a lesser-known West Central Sudanic language spoken by the Mangayat people in parts of South Sudan.
  • E. Madjingay language
    The Madjingay language is a member of the Sara language group spoken in parts of Central Africa, primarily in Chad.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decaa083e481908336d58d026eec32 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b9e8a08190bc736ac207b77324 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.