Triple

T9182859
Position Surface form Disambiguated ID Type / Status
Subject Saga Prefecture E220376 entity
Predicate contains P35 FINISHED
Object Kashima
Kashima is a city in Japan’s Kyushu region known for its traditional sake breweries and scenic coastal and rural landscapes.
 E842944 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: Kashima | Statement: [Saga Prefecture, contains, Kashima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kashima
Context triple: [Saga Prefecture, contains, Kashima]
  • A. Kashiwa
    Kashiwa is a city in Chiba Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
  • B. Kirishi
    Kirishi is an industrial town in northwestern Russia known for its major oil refinery and chemical industries.
  • C. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • D. Fujieda
    Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
  • E. Kisarazu
    Kisarazu is a coastal city in Chiba Prefecture, Japan, known as the mainland terminus of the Tokyo Bay Aqua-Line expressway.
  • 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: Kashima
Triple: [Saga Prefecture, contains, Kashima]
Generated description
Kashima is a city in Japan’s Kyushu region known for its traditional sake breweries and scenic coastal and rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kashima
Target entity description: Kashima is a city in Japan’s Kyushu region known for its traditional sake breweries and scenic coastal and rural landscapes.
  • A. Kashiwa
    Kashiwa is a city in Chiba Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
  • B. Kirishi
    Kirishi is an industrial town in northwestern Russia known for its major oil refinery and chemical industries.
  • C. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • D. Fujieda
    Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
  • E. Kisarazu
    Kisarazu is a coastal city in Chiba Prefecture, Japan, known as the mainland terminus of the Tokyo Bay Aqua-Line expressway.
  • 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_69ca83e6d77c81909862b7afef56b1bf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccc2553e548190898434aeda517407 completed April 1, 2026, 6:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cb039ff0819099ae19420cc1987a completed April 5, 2026, 8:50 p.m.
NEDg Description generation batch_69d2cd242ed8819097895cb15cbb5d47 completed April 5, 2026, 8:59 p.m.
NED2 Entity disambiguation (via description) batch_69d2d1204f008190a9349c071c1e8d19 completed April 5, 2026, 9:16 p.m.
Created at: March 30, 2026, 7:23 p.m.