Triple

T28200559
Position Surface form Disambiguated ID Type / Status
Subject E3 series Shinkansen E716870 entity
Predicate seriesVariant P13477 FINISHED
Object E3-0 series
The E3-0 series is an early variant of Japan’s E3 Shinkansen trains, designed for mini-shinkansen services with narrower car bodies suitable for converted conventional lines.
 E1809158 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: E3-0 series | Statement: [E3 series Shinkansen, seriesVariant, E3-0 series]
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: E3-0 series
Triple: [E3 series Shinkansen, seriesVariant, E3-0 series]
Generated description
The E3-0 series is an early variant of Japan’s E3 Shinkansen trains, designed for mini-shinkansen services with narrower car bodies suitable for converted conventional lines.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: seriesVariant
Context triple: [E3 series Shinkansen, seriesVariant, E3-0 series]
  • A. hasVariantSeries chosen
    Indicates a relationship where one entity is a variant or alternative series derived from or associated with another series.
  • B. seriesCode
    Indicates that an entity is assigned a specific code identifying the series or collection to which it belongs.
  • C. seriesOf
    Indicates that one entity is a sequence or ordered set of related items, events, or parts that collectively form or belong to another entity.
  • D. seriesBy
    Indicates that one entity is the creator, author, or originator of a series to which the other entity belongs.
  • E. seriesWith
    Indicates that one entity is part of, or grouped together in, the same series or sequence as 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_69efd6b826908190857e6e7dad74ed93 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f6b49436b0819094e21603054d05d4 completed May 3, 2026, 2:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a15e6b50c18819099041cfd31f2a6d5 completed May 26, 2026, 6:30 p.m.
NEDg Description generation batch_6a15eec2ef9081908b5a99d7900eb82f completed May 26, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_6a15f40d69c48190ab96b08d36dcd904 completed May 26, 2026, 7:27 p.m.
PD Predicate disambiguation batch_69f6b3a5fd8481909433e923c5e24e55 completed May 3, 2026, 2:32 a.m.
Created at: April 27, 2026, 10:31 p.m.