Triple

T5949686
Position Surface form Disambiguated ID Type / Status
Subject San Marcos Department E132365 entity
Predicate ethnicGroup P194 FINISHED
Object Mam Maya E86612 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 Maya | Statement: [San Marcos Department, ethnicGroup, Mam Maya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mam Maya
Context triple: [San Marcos Department, ethnicGroup, Mam Maya]
  • A. Majha
    Majha is a culturally significant region of Punjab in northern India, traditionally known as the heartland of Sikh culture and history.
  • B. Mamayi
    Mamayi was a powerful 14th-century military and political leader of the Golden Horde who played a central role in its internal power struggles and conflicts with emerging Russian principalities.
  • C. Maamme
    Maamme is the national anthem of Finland, known for its patriotic lyrics and prominent role in Finnish national ceremonies and sporting events.
  • D. Mam chosen
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • E. Anandamoyi
    Anandamoyi is a central character in Rabindranath Tagore’s novel "Gora," known for her deep spirituality, maternal compassion, and pivotal influence on the protagonist’s moral and religious awakening.
  • 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.