Triple

T18809172
Position Surface form Disambiguated ID Type / Status
Subject M1 Princes Motorway E459959 entity
Predicate roadNumber P1864 FINISHED
Object M1
M1 is a major British motorway that runs north–south, linking London with key cities in the Midlands and northern England.
E418454 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: M1 | Statement: [M1 Princes Motorway, roadNumber, M1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M1
Context triple: [M1 Princes Motorway, roadNumber, M1]
  • A. M1
    M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
  • B. M1
    M1 is one of the main lines of the Copenhagen Metro, providing rapid transit service through central Copenhagen and connecting key residential and commercial areas.
  • C. M1
    M1 is one of the main metro lines in the Helsinki public transport system, serving key districts across the Helsinki metropolitan area.
  • D. M1
    M1 is a major north–south urban freeway in Johannesburg, South Africa, connecting the city center with key suburbs and routes.
  • E. M1
    M1 is the main primary mirror of the Extremely Large Telescope, responsible for collecting and focusing incoming light for its observations.
  • 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: M1
Triple: [M1 Princes Motorway, roadNumber, M1]
Generated description
M1 is a major British motorway that runs north–south, linking London with key cities in the Midlands and northern England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: M1
Target entity description: M1 is a major British motorway that runs north–south, linking London with key cities in the Midlands and northern England.
  • A. M1 chosen
    M1 is a major north–south motorway in England connecting London with Leeds and forming a key part of the UK’s primary road network.
  • B. M1
    M1 is a major Irish motorway that connects Dublin to the border with Northern Ireland, forming part of the primary route between the Republic of Ireland and Belfast.
  • C. M1
    M1 is a major motorway in New South Wales, Australia, forming a key part of the coastal route between Sydney and the state's northern and southern regions.
  • D. M1
    M1 is a major north–south urban freeway in Johannesburg, South Africa, connecting the city center with key suburbs and routes.
  • E. M1
    M1 is a major Hungarian motorway that connects the capital city Budapest with the Austrian border, forming part of a key international transport corridor.
  • F. None of above.

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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3d9c49c8190a9d29a25f0c977b2 completed April 20, 2026, 3:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a055bc1fc4881909628d71314b4d76a completed May 14, 2026, 5:21 a.m.
NEDg Description generation batch_6a055f4a93f4819092054e1a4f49fef1 completed May 14, 2026, 5:36 a.m.
NED2 Entity disambiguation (via description) batch_6a055feac66c819095d9b852086296b5 completed May 14, 2026, 5:38 a.m.
Created at: April 10, 2026, 11:53 a.m.