Triple

T10247916
Position Surface form Disambiguated ID Type / Status
Subject Teke languages E240265 entity
Predicate hasMember P10 FINISHED
Object Teke-Mbere language E240261 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: Teke-Mbere language | Statement: [Teke languages, hasMember, Teke-Mbere language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teke-Mbere language
Context triple: [Teke languages, hasMember, Teke-Mbere language]
  • A. Teke–Mbede languages chosen
    The Teke–Mbede languages are a group of closely related Bantu languages spoken primarily in Gabon and neighboring Central African countries.
  • B. Bembe language
    The Bembe language is a Bantu language spoken primarily by the Bembe people in parts of the Democratic Republic of the Congo and neighboring regions of Central Africa.
  • C. Banda-Ndélé language
    The Banda-Ndélé language is a Central Sudanic language spoken by the Banda people, primarily in the Central African Republic.
  • D. Tontemboan language
    The Tontemboan language is an Austronesian language spoken by the Tontemboan people of North Sulawesi, Indonesia, and is one of the traditional Minahasan languages of the region.
  • E. Sanglechi language
    The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d22e0d4c8190a6712859924e9d3d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71cbd67648190ba7faebd12d96ca9 completed April 9, 2026, 3:27 a.m.
Created at: April 6, 2026, 11:27 a.m.