Triple

T37893996
Position Surface form Disambiguated ID Type / Status
Subject E7 series Shinkansen E945223 entity
Predicate firstOperatorServiceArea P104835 FINISHED
Object Tokyo–Nagano
Tokyo–Nagano refers to the high-speed Shinkansen corridor in Japan connecting the capital city Tokyo with the inland city of Nagano in central Honshu.
 E2248379 NE FINISHED

How this triple was built (3 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: Tokyo–Nagano | Statement: [E7 series Shinkansen, firstOperatorServiceArea, Tokyo–Nagano]
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: Tokyo–Nagano
Triple: [E7 series Shinkansen, firstOperatorServiceArea, Tokyo–Nagano]
Generated description
Tokyo–Nagano refers to the high-speed Shinkansen corridor in Japan connecting the capital city Tokyo with the inland city of Nagano in central Honshu.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: firstOperatorServiceArea
Context triple: [E7 series Shinkansen, firstOperatorServiceArea, Tokyo–Nagano]
  • A. hasPrimaryServiceArea
    Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
  • B. areaOfService chosen
    Indicates the geographic or functional region within which a service is provided or applicable.
  • C. serviceAreaName
    Indicates the designated name of the geographic or functional area that a service covers or operates within.
  • D. typicalOperatorService
    Indicates that an entity commonly performs or provides a particular operational service in a standard or expected manner.
  • E. primaryOperator
    Indicates that an entity serves as the main or leading operator responsible for performing or overseeing a specified operation or process in relation to another entity.
  • F. None of above.

Provenance (6 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_69f76ef0e8708190987c7254ed8c7abe completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_6a037c903be48190a2fafa53d7d50d42 completed May 12, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a410cc2b2d0819089452438fd41c600 completed June 28, 2026, noon
NEDg Description generation batch_6a410d70ba0c8190bdcab9e762c92884 completed June 28, 2026, 12:02 p.m.
NED2 Entity disambiguation (via description) batch_6a410e3dd828819099fc3a413bcfbeb9 completed June 28, 2026, 12:06 p.m.
PD Predicate disambiguation batch_6a037a192a008190a9917688a9e804f4 completed May 12, 2026, 7:06 p.m.
Created at: May 3, 2026, 4:19 p.m.