Triple

T6557976
Position Surface form Disambiguated ID Type / Status
Subject Mamfe languages E152498 entity
Predicate closelyRelated P37 FINISHED
Object Kendem language E602485 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: Kendem language | Statement: [Mamfe languages, closelyRelated, Kendem language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kendem language
Context triple: [Mamfe languages, closelyRelated, Kendem language]
  • A. Kendem language chosen
    The Kendem language is a Bantoid language of the Mamfe group spoken by a small community in southwestern Cameroon.
  • B. Nendö language
    The Nendö language is an Oceanic language spoken on Nendö Island in the Solomon Islands’ Temotu Province.
  • C. Damana language
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • D. Kamviri language
    The Kamviri language is a Nuristani language spoken primarily by the Kam people in parts of eastern Afghanistan and neighboring regions of Pakistan.
  • E. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • 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_69c688058d6881908c19b309cc55dbfa completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae1eb0888190a67b850ac2bca79c completed March 27, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d559ad4881909c1e7712d84945f6 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:52 p.m.