Triple

T11253963
Position Surface form Disambiguated ID Type / Status
Subject Ngbaka language E266389 entity
Predicate alternativeName P39 FINISHED
Object Ngbaka Minagende E914519 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: Ngbaka Minagende | Statement: [Ngbaka language, alternativeName, Ngbaka Minagende]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ngbaka Minagende
Context triple: [Ngbaka language, alternativeName, Ngbaka Minagende]
  • A. Ngbaka Minagende chosen
    Ngbaka Minagende is a dialect of the Ngbaka language spoken by Ngbaka communities in Central Africa.
  • B. Ngbaka Gbaya
    Ngbaka Gbaya is a dialect of the Ngbaka language spoken by the Ngbaka Gbaya people in parts of Central Africa.
  • C. Ningol Chakouba
    Ningol Chakouba is a traditional Meitei festival in Manipur that celebrates and strengthens the bond between married daughters and their parental families through ceremonial feasting and reunion.
  • D. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • E. Ngeno-Ngene
    Ngeno-Ngene is a major dialect of the Sasak language spoken on the island of Lombok in Indonesia.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9346f4c8190b29c2cf3a29cd1d1 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f40019588190864c59e8451e80bd completed April 19, 2026, 3:25 p.m.
Created at: April 8, 2026, 9:31 p.m.