Triple

T2957282
Position Surface form Disambiguated ID Type / Status
Subject Taracahitic E79962 entity
Predicate hasMember P10 FINISHED
Object Mayo language
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.
 E313516 NE FINISHED

How this triple was built (4 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: [Taracahitic, hasMember, Mayo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mayo language
Context triple: [Taracahitic, hasMember, Mayo language]
  • A. Maiwa language
    The Maiwa language is an Austronesian language spoken by the Maiwa people in South Sulawesi, Indonesia.
  • B. 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.
  • C. Mampruli language
    Mampruli is a Gur language spoken primarily by the Mamprusi people in northern Ghana and parts of neighboring West African countries.
  • D. Makushi language
    The Makushi language is an indigenous Cariban language spoken primarily by the Makushi people in northern Brazil and southern Guyana.
  • E. Moxo language
    The Moxo language is an indigenous Arawakan language spoken by the Moxo (Mojo) people of Bolivia’s lowland regions.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mayo language
Triple: [Taracahitic, hasMember, Mayo language]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mayo language
Target entity description: 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.
  • A. Maiwa language
    The Maiwa language is an Austronesian language spoken by the Maiwa people in South Sulawesi, Indonesia.
  • B. 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.
  • C. Mampruli language
    Mampruli is a Gur language spoken primarily by the Mamprusi people in northern Ghana and parts of neighboring West African countries.
  • D. Makushi language
    The Makushi language is an indigenous Cariban language spoken primarily by the Makushi people in northern Brazil and southern Guyana.
  • E. Moxo language
    The Moxo language is an indigenous Arawakan language spoken by the Moxo (Mojo) people of Bolivia’s lowland regions.
  • F. None of above. chosen

Provenance (5 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_69ad8b1276588190a374a0b12e0f7bdf completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad992b33e081909d22a19d5064c47d completed March 8, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc8a10848190b8eec482252eb76b completed March 11, 2026, 5:24 a.m.
NEDg Description generation batch_69b0fd407bd08190b62788e8d1cdd205 completed March 11, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_69b0fd91541c8190a481b55eb9b0ac35 completed March 11, 2026, 5:28 a.m.
Created at: March 8, 2026, 2:57 p.m.