Triple

T9153382
Position Surface form Disambiguated ID Type / Status
Subject Kato E219644 entity
Predicate hasScriptVariant P5922 FINISHED
Object 加東
加東 is the Japanese kanji name typically referring to the city of Katō in Hyōgo Prefecture, Japan.
 E779948 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: 加東 | Statement: [Kato, hasScriptVariant, 加東]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 加東
Context triple: [Kato, hasScriptVariant, 加東]
  • A. Nishi-Okano
    Nishi-Okano is a notable neighborhood within Nishi Ward in the city of Yokohama, Japan.
  • B. Moriyama
    Moriyama is a Japanese city located in Shiga Prefecture, known for its position near Lake Biwa and its blend of residential areas and historical sites.
  • C. Matsuda
    Matsuda is a small town in Kanagawa Prefecture, Japan, known for its scenic views of Mount Fuji and seasonal flower festivals.
  • D. Kawaguchi
    Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
  • E. Wakamatsu
    Wakamatsu is a ward in the city of Kitakyushu, Japan, known historically as a port and industrial area on the northern coast of Kyushu.
  • 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: 加東
Triple: [Kato, hasScriptVariant, 加東]
Generated description
加東 is the Japanese kanji name typically referring to the city of Katō in Hyōgo Prefecture, Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 加東
Target entity description: 加東 is the Japanese kanji name typically referring to the city of Katō in Hyōgo Prefecture, Japan.
  • A. 加東 chosen
    加東 is a Japanese place or family name commonly romanized as "Kato" or "Katō."
  • B. Nishi-Okano
    Nishi-Okano is a notable neighborhood within Nishi Ward in the city of Yokohama, Japan.
  • C. Moriyama
    Moriyama is a Japanese city located in Shiga Prefecture, known for its position near Lake Biwa and its blend of residential areas and historical sites.
  • D. Matsuda
    Matsuda is a small town in Kanagawa Prefecture, Japan, known for its scenic views of Mount Fuji and seasonal flower festivals.
  • E. Kawaguchi
    Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
  • 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_69ca83e25418819093c6503deeaf30de completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca96e323881909cbf4d6708f24f79 completed April 1, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0545c5bb48190b889e6e9ef0448a5 completed April 3, 2026, 11:59 p.m.
NEDg Description generation batch_69d05628d8708190a85437c5051a5a05 completed April 4, 2026, 12:07 a.m.
NED2 Entity disambiguation (via description) batch_69d056e4ad98819086e73edf15aa6210 completed April 4, 2026, 12:10 a.m.
Created at: March 30, 2026, 7:20 p.m.