Triple

T3812537
Position Surface form Disambiguated ID Type / Status
Subject Kyushu Shinkansen E93167 entity
Predicate serviceType P87 FINISHED
Object Tsubame
Tsubame is a Japanese Shinkansen train service that operates on the Kyushu Shinkansen line in southern Japan.
 E389801 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: Tsubame | Statement: [Kyushu Shinkansen, serviceType, Tsubame]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tsubame
Context triple: [Kyushu Shinkansen, serviceType, Tsubame]
  • A. Tsuru
    Tsuru is a small city in Yamanashi Prefecture, Japan, known for its scenic setting near Mount Fuji and its educational institutions.
  • B. Katsuragi
    Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
  • C. Katsuragi
    Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
  • D. Kawaiisu
    Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
  • E. Hōshō
    Hōshō was the Imperial Japanese Navy’s pioneering aircraft carrier and the world’s first purpose-built carrier to enter service.
  • 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: Tsubame
Triple: [Kyushu Shinkansen, serviceType, Tsubame]
Generated description
Tsubame is a Japanese Shinkansen train service that operates on the Kyushu Shinkansen line in southern Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tsubame
Target entity description: Tsubame is a Japanese Shinkansen train service that operates on the Kyushu Shinkansen line in southern Japan.
  • A. Tsuru
    Tsuru is a small city in Yamanashi Prefecture, Japan, known for its scenic setting near Mount Fuji and its educational institutions.
  • B. Katsuragi
    Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
  • C. Katsuragi
    Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
  • D. Kawaiisu
    Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
  • E. Hōshō
    Hōshō was the Imperial Japanese Navy’s pioneering aircraft carrier and the world’s first purpose-built carrier to enter service.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee8db8a288190afd1e3b9dcf02e97 completed March 9, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb3a69908190ba8e7ac37c8ca0f8 completed March 14, 2026, 6:07 a.m.
NEDg Description generation batch_69b4fbf52fc88190a54ba5b374b2cdad completed March 14, 2026, 6:11 a.m.
NED2 Entity disambiguation (via description) batch_69b4fc6847e88190b6590aa2e56c8903 completed March 14, 2026, 6:12 a.m.
Created at: March 9, 2026, 3:16 p.m.