Triple

T9916954
Position Surface form Disambiguated ID Type / Status
Subject Tōhoku Shinkansen E185892 entity
Predicate serviceType P87 FINISHED
Object Komachi E626154 NE FINISHED

How this triple was built (2 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: Komachi | Statement: [Tōhoku Shinkansen, serviceType, Komachi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Komachi
Context triple: [Tōhoku Shinkansen, serviceType, Komachi]
  • A. Mirina
    Mirina is a coastal town on the Greek island of Lemnos, serving as its capital and main port in the northern Aegean Sea.
  • B. Makiko
    Makiko is a Japanese feminine given name commonly borne by women in Japan and of Japanese heritage.
  • C. Yamabiko chosen
    Yamabiko is a high-speed Shinkansen train service in Japan that operates on the Tōhoku Shinkansen line, connecting Tokyo with northern regions such as Sendai.
  • 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. Orito
    Orito is a municipality and town located in the Putumayo Department of southwestern Colombia, known for its role in regional oil production and its position within the Amazonian foothills.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb540195881908f25f7dde5c66a75 completed April 2, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d299d479d481908dc8fe2acc307a64 completed April 5, 2026, 5:20 p.m.
Created at: March 30, 2026, 8:42 p.m.