Triple

T9162033
Position Surface form Disambiguated ID Type / Status
Subject Ga-Dangme people E219846 entity
Predicate traditionalArea P14194 FINISHED
Object Teshie E182924 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: Teshie | Statement: [Ga-Dangme people, traditionalArea, Teshie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teshie
Context triple: [Ga-Dangme people, traditionalArea, Teshie]
  • A. Teshie chosen
    Teshie is a coastal suburban town in the Greater Accra Region of Ghana, known for its vibrant Ga culture, fishing community, and annual Homowo and Kpeshie festivals.
  • B. Ikeja
    Ikeja is a major commercial and administrative hub in Nigeria, serving as the capital of Lagos State and hosting numerous businesses, government offices, and the Murtala Muhammed International Airport.
  • C. Itabashi
    Itabashi is a special ward in northern Tokyo, Japan, known as a primarily residential area with a mix of traditional neighborhoods and modern urban infrastructure.
  • D. Sumida City
    Sumida City is a special ward of Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional downtown neighborhoods.
  • E. Asakusabashi
    Asakusabashi is a district in Tokyo known for its traditional wholesale shops, craft stores, and convenient access to central city areas.
  • 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_69ca83e3633c81908688a9fa2306ba99 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccaa2c1a9881909b7100b6e436386d completed April 1, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d054770a0c819095cf0a7cc8d1a057 completed April 3, 2026, 11:59 p.m.
Created at: March 30, 2026, 7:21 p.m.