Triple

T3700567
Position Surface form Disambiguated ID Type / Status
Subject Seto Inland Sea E78567 entity
Predicate hasJapaneseName P9882 FINISHED
Object 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.
 E381055 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 Naikai | Statement: [Seto Inland Sea, hasJapaneseName, Seto Naikai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Seto Naikai
Context triple: [Seto Inland Sea, hasJapaneseName, Seto Naikai]
  • 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. Shimamoto
    Shimamoto is a town in Osaka Prefecture, Japan, located between Kyoto and Osaka along the Yodo River.
  • D. Arakawa
    Arakawa is a special ward in Tokyo, Japan, known for its mix of traditional residential neighborhoods and industrial areas along the Arakawa River.
  • E. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • 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 Naikai
Triple: [Seto Inland Sea, hasJapaneseName, Seto Naikai]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Seto Naikai
Target entity description: 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.
  • 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. Shimamoto
    Shimamoto is a town in Osaka Prefecture, Japan, located between Kyoto and Osaka along the Yodo River.
  • D. Arakawa
    Arakawa is a special ward in Tokyo, Japan, known for its mix of traditional residential neighborhoods and industrial areas along the Arakawa River.
  • E. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • F. None of above. chosen

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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc514eb6c8190b3b74a603c717729 completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3df86bc819088db92eecee69fd3 completed March 14, 2026, 2:11 a.m.
NEDg Description generation batch_69b4c7e579d4819090edfa8a858c40c4 completed March 14, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69b4c86511e48190872b3d85019bc013 completed March 14, 2026, 2:31 a.m.
Created at: March 8, 2026, 3:26 p.m.