Triple

T5949682
Position Surface form Disambiguated ID Type / Status
Subject San Marcos Department E132365 entity
Predicate languageUsed P238 FINISHED
Object Mam language E388690 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: Mam language | Statement: [San Marcos Department, languageUsed, Mam language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mam language
Context triple: [San Marcos Department, languageUsed, Mam language]
  • A. Mam language chosen
    Mam language is a Mayan language spoken primarily by the Mam people in the highland regions of Guatemala and parts of southern Mexico.
  • B. Mamulique language
    The Mamulique language is an extinct and poorly documented indigenous language once spoken in northeastern Mexico, generally classified within the Coahuiltecan group.
  • C. Mambae language
    The Mambae language is an Austronesian language spoken primarily in East Timor, notable for its role in local identity and traditional culture.
  • D. Mamfe languages
    The Mamfe languages are a small group of closely related Niger-Congo languages spoken primarily in the Mamfe region of southwestern Cameroon.
  • E. Mampruli language
    Mampruli is a Gur language spoken primarily by the Mamprusi people in northern Ghana and parts of neighboring West African countries.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0397fd19081908ab31b190deb8247 completed March 22, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3cb29f8819095d44ae3ad193fb2 completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:02 p.m.