Triple

T22720236
Position Surface form Disambiguated ID Type / Status
Subject Hohoe E561838 entity
Predicate languageSpoken P151 FINISHED
Object Ewe 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: Ewe | Statement: [Hohoe, languageSpoken, Ewe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ewe
Context triple: [Hohoe, languageSpoken, Ewe]
  • A. Ewe chosen
    Ewe is a major Niger–Congo language spoken primarily in southeastern Ghana and southern Togo by the Ewe people.
  • B. Mòoré
    Mòoré is a major Gur language spoken primarily by the Mossi people in Burkina Faso and surrounding West African countries.
  • C. Ewenke
    Ewenke is an alternative name for the Evenki language, a Tungusic language spoken by the Evenki people of Siberia and parts of China and Mongolia.
  • D. Fante people
    The Fante people are a major Akan ethnic group from Ghana’s coastal region, known for their historic trading states, rich cultural traditions, and significant influence in Ghanaian politics and education.
  • E. Akposso people
    The Akposso people are an ethnic group of Togo (and neighboring areas) known for their distinct cultural traditions and use of the Ikposo language.
  • 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_69e2454fc984819088213b58ee87a002 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17910deb48190b38174e16868f3dd completed April 29, 2026, 3:20 a.m.
Created at: April 17, 2026, 3:19 p.m.