Triple

T23437814
Position Surface form Disambiguated ID Type / Status
Subject Benesse House Park E563511 entity
Predicate accessibleFrom P1985 FINISHED
Object Uno Port 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: Uno Port | Statement: [Benesse House Park, accessibleFrom, Uno Port]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uno Port
Context triple: [Benesse House Park, accessibleFrom, Uno Port]
  • A. Uno Port chosen
    Uno Port is a coastal port area in Tamano, Okayama Prefecture, Japan, serving as a key gateway to the islands of the Seto Inland Sea and a primary access point for contemporary art events and tourism.
  • B. Uno
    Uno is a compact city car model produced by the Italian automaker Fiat.
  • C. Uno
    Uno is one of the islands in Guinea-Bissau’s Bijagós Archipelago, a coastal island group in West Africa known for its rich biodiversity and traditional communities.
  • D. Uno
    Uno is a popular shedding-type card game in which players race to discard all their cards by matching colors or numbers and using special action cards.
  • E. Uno
    Uno is a Norwegian crime drama film best known for starring and being co-written by actor-director Aksel Hennie.
  • 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_69e24553980c8190bb66a2ae0bdab125 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5dda7448190b6c686e0db4f4f2f completed April 29, 2026, 6:31 a.m.
Created at: April 17, 2026, 5:50 p.m.