Triple

T12834632
Position Surface form Disambiguated ID Type / Status
Subject Akamkpa E306875 entity
Predicate roadConnection P385 FINISHED
Object Ikom E306871 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: Ikom | Statement: [Akamkpa, roadConnection, Ikom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ikom
Context triple: [Akamkpa, roadConnection, Ikom]
  • A. Ikom chosen
    Ikom is a prominent commercial and administrative town in southeastern Nigeria known for its cocoa production and strategic location near the Cameroon border.
  • B. Oimachi
    Oimachi is a commercial and residential district in Tokyo known for its busy train hub, shopping streets, and convenient access to central Shinagawa and other parts of the city.
  • C. Kōta
    Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
  • D. Ikoma
    Ikoma is a city in Japan known for its scenic setting on the slopes of Mount Ikoma and its role as a residential and commuter hub near Osaka and Nara.
  • E. Ibuka
    Ibuka is a Japanese surname most notably associated with Masaru Ibuka, the co-founder of Sony Corporation.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96fb1c7248190bb6e644e041d192e completed April 10, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68edaa6288190a775f6e852fa941b completed May 2, 2026, 11:55 p.m.
Created at: April 9, 2026, 5:34 p.m.