Triple

T9988804
Position Surface form Disambiguated ID Type / Status
Subject Department of Linguistics, University of Chile E196833 entity
Predicate focusesOnLanguage P56443 FINISHED
Object Mapudungun E234600 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: Mapudungun | Statement: [Department of Linguistics, University of Chile, focusesOnLanguage, Mapudungun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mapudungun
Context triple: [Department of Linguistics, University of Chile, focusesOnLanguage, Mapudungun]
  • A. Mapudungun chosen
    Mapudungun is an indigenous language of South America spoken primarily by the Mapuche people in Chile and Argentina.
  • B. Puel Mapu
    Puel Mapu is the eastern portion of the ancestral Mapuche territory, located mainly in what is now Argentina.
  • C. Mazabuka
    Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
  • D. Ngulu Mapu
    Ngulu Mapu is the eastern, Argentine sector of the ancestral Mapuche territory within the broader region known as Wallmapu.
  • E. Mwotlap
    Mwotlap is an Oceanic Austronesian language spoken on Mota Lava and nearby islands in northern Vanuatu.
  • 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_69ca82f1678c819093d06320a05f16a4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdc79e10408190bcb4e55b6a0df79c completed April 2, 2026, 1:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b5e243548190b77328b5ce9e8028 completed April 5, 2026, 7:20 p.m.
Created at: March 30, 2026, 8:50 p.m.