Triple

T10014923
Position Surface form Disambiguated ID Type / Status
Subject Aichi Prefecture E199464 entity
Predicate containsCity P294 FINISHED
Object Seto
Seto is a Japanese city renowned as one of the country’s major traditional pottery and ceramics centers.
 E248953 NE FINISHED

How this triple was built (4 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: Seto | Statement: [Aichi Prefecture, containsCity, Seto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Seto
Context triple: [Aichi Prefecture, containsCity, Seto]
  • A. Seto
    Seto is a South Estonian dialect and cultural variety spoken by the Seto people, known for its distinct linguistic features and rich folk traditions.
  • B. Seto
    Seto is a city in Kagawa Prefecture, Japan, known for its traditional ceramics and role as a regional cultural and industrial center.
  • C. Seto Naikai
    Seto Naikai is a scenic body of water in western Japan, dotted with islands and known for its mild climate, historic trade routes, and picturesque coastal landscapes.
  • D. Ninoshima
    Ninoshima is a small island in Japan known for its location near Hiroshima and its historical role during and after the atomic bombing of Hiroshima in World War II.
  • E. Nambui
    Nambui was a Mongol empress consort of the Yuan dynasty and a prominent wife of Kublai Khan, influential in the imperial court after the death of his first empress.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Seto
Triple: [Aichi Prefecture, containsCity, Seto]
Generated description
Seto is a Japanese city renowned as one of the country’s major traditional pottery and ceramics centers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Seto
Target entity description: Seto is a Japanese city renowned as one of the country’s major traditional pottery and ceramics centers.
  • A. Seto
    Seto is a South Estonian dialect and cultural variety spoken by the Seto people, known for its distinct linguistic features and rich folk traditions.
  • B. Seto chosen
    Seto is a city in Kagawa Prefecture, Japan, known for its traditional ceramics and role as a regional cultural and industrial center.
  • C. Seto Naikai
    Seto Naikai is a scenic body of water in western Japan, dotted with islands and known for its mild climate, historic trade routes, and picturesque coastal landscapes.
  • D. Ninoshima
    Ninoshima is a small island in Japan known for its location near Hiroshima and its historical role during and after the atomic bombing of Hiroshima in World War II.
  • E. Nambui
    Nambui was a Mongol empress consort of the Yuan dynasty and a prominent wife of Kublai Khan, influential in the imperial court after the death of his first empress.
  • F. None of above.

Provenance (5 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd49b19c8190b429e3533d072648 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a8f6f3081909310e28725d31f7e completed April 5, 2026, 1:58 p.m.
NEDg Description generation batch_69d26b84271881909c3a1b8a05e2c8a2 completed April 5, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_69d26f50dc008190866f0ba45b671560 completed April 5, 2026, 2:18 p.m.
Created at: March 30, 2026, 8:52 p.m.