Triple

T21473410
Position Surface form Disambiguated ID Type / Status
Subject Maringe Lagoon area E529789 entity
Predicate languageSpoken P151 FINISHED
Object Cheke Holo 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: Cheke Holo | Statement: [Maringe Lagoon area, languageSpoken, Cheke Holo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheke Holo
Context triple: [Maringe Lagoon area, languageSpoken, Cheke Holo]
  • A. Cheke Holo chosen
    Cheke Holo is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
  • B. Chekka
    Chekka is a coastal town in northern Lebanon known for its beaches, industrial facilities, and location along the Mediterranean Sea.
  • C. Chekecha Cheketua
    Chekecha Cheketua is a popular Tanzanian Bongo Flava hit song by Ali Kiba known for its catchy melody and danceable rhythm.
  • D. Songololo
    Songololo is a town in the western Democratic Republic of the Congo, situated near the border with Angola and known as a local transport and trade hub.
  • E. Hosaena
    Hosaena is a town in southern Ethiopia that serves as an important administrative and commercial center in the Southern Nations, Nationalities, and Peoples' Region.
  • 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_69e0c459acb481909bb6ee452a0045c7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea156dac819087c4594d022d3df6 completed April 23, 2026, 9:44 a.m.
Created at: April 16, 2026, 6:19 p.m.