Triple

T16177750
Position Surface form Disambiguated ID Type / Status
Subject Battle of Millarapue E392607 entity
Predicate hasLanguage P15 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: [Battle of Millarapue, hasLanguage, Mapudungun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mapudungun
Context triple: [Battle of Millarapue, hasLanguage, 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. Mabasa
    Mabasa is a barangay (village-level administrative division) within the municipality of Argao in Cebu, Philippines.
  • E. Mapusa
    Mapusa is a bustling commercial town in North Goa, India, known as a major market and transport hub near the popular beaches of the state.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22059e7048190b4592cb1516b5f8d completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69fffefe4dc08190a6cc43a448ae6554 completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 5:02 a.m.