Triple

T1945898
Position Surface form Disambiguated ID Type / Status
Subject Austroasiatic E42054 entity
Predicate hasLanguage P15 FINISHED
Object Mon language E216899 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: Mon language | Statement: [Austroasiatic, hasLanguage, Mon language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mon language
Context triple: [Austroasiatic, hasLanguage, Mon language]
  • A. Mon language chosen
    Mon language is an Austroasiatic language historically spoken in parts of Myanmar and Thailand, notable for its ancient literary tradition and influence on regional scripts and cultures.
  • B. Mono language
    Mono language is a Native American Uto-Aztecan language traditionally spoken by the Mono people of eastern California.
  • C. Hoanya language
    The Hoanya language is an extinct Austronesian language once spoken by the Hoanya people of western Taiwan and classified among the indigenous Formosan languages.
  • D. Amuesha language
    The Amuesha language, also known as Yanesha', is an Arawakan language spoken by the Yanesha' people of the central Peruvian Amazon.
  • E. Limba
    The Limba are one of the largest and oldest indigenous ethnic groups in Sierra Leone, known for their distinct language, cultural traditions, and historical role in the country’s northern regions.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb300af2481908ae359972843c1ef completed March 7, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbbcc5688190aad081dc8d119e7f completed March 8, 2026, 10:44 p.m.
Created at: March 4, 2026, 7:36 p.m.