Triple

T3042564
Position Surface form Disambiguated ID Type / Status
Subject Northern Uto-Aztecan E83164 entity
Predicate containsLanguage P2177 FINISHED
Object Mayo language E313516 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: Mayo language | Statement: [Northern Uto-Aztecan, containsLanguage, Mayo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mayo language
Context triple: [Northern Uto-Aztecan, containsLanguage, Mayo language]
  • A. Mayo language chosen
    The Mayo language is an indigenous Uto-Aztecan language spoken primarily by the Mayo people of northern Mexico, especially in the states of Sonora and Sinaloa.
  • B. Maiwa language
    The Maiwa language is an Austronesian language spoken by the Maiwa people in South Sulawesi, Indonesia.
  • C. Marau language
    The Marau language is an Oceanic language spoken in the Solomon Islands, belonging to the Southeast Solomonic branch of the Austronesian language family.
  • D. Mampruli language
    Mampruli is a Gur language spoken primarily by the Mamprusi people in northern Ghana and parts of neighboring West African countries.
  • E. Makushi language
    The Makushi language is an indigenous Cariban language spoken primarily by the Makushi people in northern Brazil and southern Guyana.
  • 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_69ad8b2298908190a7cb4e9bdbf064d0 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b5d2a308190b4ce20efcae9b761 completed March 8, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ded35e008190be7dd72aa7537a3b completed March 11, 2026, 9:29 p.m.
Created at: March 8, 2026, 3:01 p.m.