Triple

T10624578
Position Surface form Disambiguated ID Type / Status
Subject Imabari Shipbuilding Saijo shipyard E250288 entity
Predicate locatedInMunicipality P40 FINISHED
Object Saijo
Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
 E1063390 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: Saijo | Statement: [Imabari Shipbuilding Saijo shipyard, locatedInMunicipality, Saijo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saijo
Context triple: [Imabari Shipbuilding Saijo shipyard, locatedInMunicipality, Saijo]
  • A. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • B. 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.
  • C. Semboku
    Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
  • D. Ikawai
    Ikawai is a small rural settlement in the Waimate District of the Canterbury region on New Zealand’s South Island.
  • E. Miyoshi
    Miyoshi is a Japanese city known for its scenic river valleys, historical sites, and cultural exchanges with its international sister cities.
  • 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: Saijo
Triple: [Imabari Shipbuilding Saijo shipyard, locatedInMunicipality, Saijo]
Generated description
Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saijo
Target entity description: Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
  • A. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • B. 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.
  • C. Semboku
    Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
  • D. Ikawai
    Ikawai is a small rural settlement in the Waimate District of the Canterbury region on New Zealand’s South Island.
  • E. Miyoshi
    Miyoshi is a Japanese city known for its scenic river valleys, historical sites, and cultural exchanges with its international sister cities.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df7fe9fc81908b3b8d1dc06a829c completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8bcbb34819088c21d79357eef8a completed May 3, 2026, 9:06 p.m.
NEDg Description generation batch_69f7b974fce88190ace5030555b7b5f1 completed May 3, 2026, 9:09 p.m.
NED2 Entity disambiguation (via description) batch_69f7ba99ad9c8190906b6b63cf27a446 completed May 3, 2026, 9:14 p.m.
Created at: April 8, 2026, 8:53 p.m.