Triple

T14424003
Position Surface form Disambiguated ID Type / Status
Subject Lolo-Burmese E357649 entity
Predicate includes P1393 FINISHED
Object Zaiwa language E644036 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: Zaiwa language | Statement: [Lolo-Burmese, includes, Zaiwa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaiwa language
Context triple: [Lolo-Burmese, includes, Zaiwa language]
  • A. Zaiwa language chosen
    The Zaiwa language is a Tibeto-Burman language spoken primarily by the Zaiwa people in parts of Yunnan, China and northern Myanmar.
  • B. Sayawa language
    The Sayawa language is a Chadic language spoken primarily by the Sayawa people in Bauchi State, northeastern Nigeria.
  • C. Tiwa language
    Tiwa language is a Tibeto-Burman language spoken by the Tiwa (Lalung) people of northeastern India, primarily in Assam and Meghalaya.
  • D. Zay language
    Zay language is a South Ethiopic Semitic language spoken by the Zay people on islands and shores of Lake Zway in Ethiopia.
  • E. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91123f848190ba3fb18a76c2d24c completed April 14, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bcd2a908190ad7d5ebf11b41551 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:18 a.m.