Triple

T21830261
Position Surface form Disambiguated ID Type / Status
Subject Arhuaco language E538974 entity
Predicate closelyRelatedTo P37 FINISHED
Object Damana language NE NERFINISHED

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: Damana language | Statement: [Arhuaco language, closelyRelatedTo, Damana language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Damana language
Context triple: [Arhuaco language, closelyRelatedTo, Damana language]
  • A. Damana language chosen
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • B. Tanema language
    Tanema is a nearly extinct Oceanic language once spoken on Vanikoro Island in the Temotu Province of the Solomon Islands.
  • C. Damara language
    The Damara language is a Khoe (Central Khoisan) language spoken primarily by the Damara people of Namibia.
  • D. Badimaya language
    Badimaya language is an Australian Aboriginal language traditionally spoken by the Yamatji people of Western Australia.
  • E. Daakaka language
    The Daakaka language is an Oceanic language spoken by communities on Ambrym Island in Vanuatu.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0913554508190b81347f01d3903e8 completed April 28, 2026, 10:51 a.m.
Created at: April 16, 2026, 6:54 p.m.