Triple

T19166414
Position Surface form Disambiguated ID Type / Status
Subject Anyako, Ghana E469194 entity
Predicate locatedNear P294 FINISHED
Object Anloga 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: Anloga | Statement: [Anyako, Ghana, locatedNear, Anloga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anloga
Context triple: [Anyako, Ghana, locatedNear, Anloga]
  • A. Anloga chosen
    Anloga is a coastal town in southeastern Ghana that serves as the traditional and administrative center of the Anlo Ewe people in the Volta Region.
  • B. Anozie
    Anozie is the surname of British-Nigerian actor Nonso Anozie, known for his roles in film, television, and theatre.
  • C. Anúna
    Anúna is an Irish choral ensemble known for its ethereal vocal style and fusion of traditional Celtic music with contemporary choral arrangements.
  • D. Agelo
    Agelo is a small rural village in the Dutch province of Overijssel, known for its agricultural landscape and traditional countryside character.
  • E. Anini
    Anini is a remote town in the Dibang Valley district of Arunachal Pradesh in northeastern India, known for its rugged Himalayan terrain and proximity to the Dibang River.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f15ee064819087f9fd822236298f completed April 20, 2026, 9:26 a.m.
Created at: April 10, 2026, 12:06 p.m.