Triple

T11567047
Position Surface form Disambiguated ID Type / Status
Subject Atsugi E274278 entity
Predicate river P165 FINISHED
Object Nakatsugawa
Nakatsugawa is a river associated with the city of Atsugi in Kanagawa Prefecture, Japan.
 E1050433 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: Nakatsugawa | Statement: [Atsugi, river, Nakatsugawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nakatsugawa
Context triple: [Atsugi, river, Nakatsugawa]
  • A. Gushikawa
    Gushikawa was a former city in Okinawa Prefecture, Japan, that later became part of the modern city of Uruma.
  • B. Kakogawa
    Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
  • C. Hommachi
    Hommachi is a major commercial and business district in central Osaka, Japan, known for its offices, shops, and convenient subway connections.
  • D. Suruga Kanbaru
    Suruga Kanbaru is a spirited, athletic high school girl and former basketball star from the Monogatari Series, known for her monkey’s paw curse, rapid-fire speech, and open admiration for her senior Hitagi Senjougahara.
  • E. Ayagawa
    Ayagawa is a small town in Kagawa Prefecture on Japan’s Shikoku island, known for its rural landscapes and traditional agricultural character.
  • 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: Nakatsugawa
Triple: [Atsugi, river, Nakatsugawa]
Generated description
Nakatsugawa is a river associated with the city of Atsugi in Kanagawa Prefecture, Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nakatsugawa
Target entity description: Nakatsugawa is a river associated with the city of Atsugi in Kanagawa Prefecture, Japan.
  • A. Gushikawa
    Gushikawa was a former city in Okinawa Prefecture, Japan, that later became part of the modern city of Uruma.
  • B. Kakogawa
    Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
  • C. Hommachi
    Hommachi is a major commercial and business district in central Osaka, Japan, known for its offices, shops, and convenient subway connections.
  • D. Suruga Kanbaru
    Suruga Kanbaru is a spirited, athletic high school girl and former basketball star from the Monogatari Series, known for her monkey’s paw curse, rapid-fire speech, and open admiration for her senior Hitagi Senjougahara.
  • E. Ayagawa
    Ayagawa is a small town in Kagawa Prefecture on Japan’s Shikoku island, known for its rural landscapes and traditional agricultural character.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd4305c8190ac5ff490b6b63e12 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69f77f6baca4819080f85da5fe0c2aba completed May 3, 2026, 5:01 p.m.
NEDg Description generation batch_69f78125632881908d601ee4c4aaae35 completed May 3, 2026, 5:08 p.m.
NED2 Entity disambiguation (via description) batch_69f781e32cb48190abc83e65405ac8ac completed May 3, 2026, 5:12 p.m.
Created at: April 8, 2026, 9:37 p.m.