Triple

T16024813
Position Surface form Disambiguated ID Type / Status
Subject Mam language E388690 entity
Predicate hasDialects P4251 FINISHED
Object Northern Mam E411183 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: Northern Mam | Statement: [Mam language, hasDialects, Northern Mam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Northern Mam
Context triple: [Mam language, hasDialects, Northern Mam]
  • A. Northern Mam chosen
    Northern Mam is a Mayan language variety spoken primarily in the highland regions of Guatemala by Mam indigenous communities.
  • B. Northern Anii
    Northern Anii is a regional variety of the Anii language spoken by communities in the northern part of the Anii-speaking area of West Africa.
  • C. March North
    March North is an electoral ward in the town of March, Cambridgeshire, represented on the local council.
  • D. Northern Uma
    Northern Uma is a regional dialect of the Uma language spoken by communities in Central Sulawesi, Indonesia.
  • E. Northern Dimlî
    Northern Dimlî is a regional variety of the Dimlî (Zaza) language spoken primarily in the northern parts of its traditional area in eastern Turkey.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183258c708190acf1588c7ccb254c completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf31c8d8819096c562ba1453f3c0 completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:55 a.m.