Triple

T2310486
Position Surface form Disambiguated ID Type / Status
Subject Nova (TransPennine Express) E51944 entity
Predicate hasSubfleet P37971 FINISHED
Object Nova 3
Nova 3 is a subfleet of modern intercity train sets operated by TransPennine Express in the UK, designed to provide higher-capacity, long-distance services.
E256312 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: Nova 3 | Statement: [Nova (TransPennine Express), hasSubfleet, Nova 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nova 3
Context triple: [Nova (TransPennine Express), hasSubfleet, Nova 3]
  • A. Pixel 3a
    The Pixel 3a is a mid-range Android smartphone by Google known for delivering flagship-level camera performance at a lower price point.
  • B. Moto G
    Moto G is a popular line of budget-friendly Android smartphones known for offering strong performance and features at an affordable price.
  • C. Moto Z
    Moto Z is a line of modular Android smartphones by Motorola known for its ultra-thin design and support for snap-on Moto Mods accessories.
  • D. Nokia X
    Nokia X is a line of budget smartphones by Nokia that ran a customized version of Android with a Windows Phone–inspired interface.
  • E. Google Pixel 3
    Google Pixel 3 is a flagship Android smartphone by Google known for its advanced computational photography features and clean software experience.
  • 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: Nova 3
Triple: [Nova (TransPennine Express), hasSubfleet, Nova 3]
Generated description
Nova 3 is a subfleet of modern intercity train sets operated by TransPennine Express in the UK, designed to provide higher-capacity, long-distance services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nova 3
Target entity description: Nova 3 is a subfleet of modern intercity train sets operated by TransPennine Express in the UK, designed to provide higher-capacity, long-distance services.
  • A. Pixel 3a
    The Pixel 3a is a mid-range Android smartphone by Google known for delivering flagship-level camera performance at a lower price point.
  • B. Moto G
    Moto G is a popular line of budget-friendly Android smartphones known for offering strong performance and features at an affordable price.
  • C. Moto Z
    Moto Z is a line of modular Android smartphones by Motorola known for its ultra-thin design and support for snap-on Moto Mods accessories.
  • D. Nokia X
    Nokia X is a line of budget smartphones by Nokia that ran a customized version of Android with a Windows Phone–inspired interface.
  • E. Google Pixel 3
    Google Pixel 3 is a flagship Android smartphone by Google known for its advanced computational photography features and clean software experience.
  • 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_69a88b0bb30c81908ded03b006d29387 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abd0d6b0e48190aee9131ca182e52f completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8959d860819095ea3113e3d9264e completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8d49b7c081909f89c71a56067458 completed March 9, 2026, 9:05 a.m.
NED2 Entity disambiguation (via description) batch_69ae8dc4cf44819082f242d6806aa45a completed March 9, 2026, 9:07 a.m.
Created at: March 4, 2026, 7:49 p.m.