Triple

T22570436
Position Surface form Disambiguated ID Type / Status
Subject Mon civilization E558060 entity
Predicate language P15 FINISHED
Object Mon language 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: Mon language | Statement: [Mon civilization, language, Mon language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mon language
Context triple: [Mon civilization, language, 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. Mono language
    Mono is an Oceanic language spoken by the Mono people of the Treasury Islands in the Solomon Islands.
  • D. Nomatsiguenga language
    The Nomatsiguenga language is an Arawakan language spoken by the Nomatsiguenga people of Peru’s Amazon rainforest, closely associated with the broader Asháninka linguistic and cultural group.
  • E. Camorta language
    The Camorta language is an Austroasiatic language spoken by the Nicobarese people on Camorta Island in India’s Nicobar Islands.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fad35448190b51a3dd639ca8568 completed April 29, 2026, 1:32 a.m.
Created at: April 16, 2026, 8:52 p.m.