Triple

T18101849
Position Surface form Disambiguated ID Type / Status
Subject M1 motorway E433238 entity
Predicate roadNumberingScheme P1864 FINISHED
Object M1
M1 is a major north–south motorway in England connecting London to Leeds and forming a key part of the UK’s primary road network.
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 motorway, roadNumberingScheme, M1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M1
Context triple: [M1 motorway, roadNumberingScheme, 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 motorway, roadNumberingScheme, M1]
Generated description
M1 is a major north–south motorway in England connecting London to Leeds and forming a key part of the UK’s primary road network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: M1
Target entity description: M1 is a major north–south motorway in England connecting London to Leeds and forming a key part of the UK’s primary road network.
  • 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 Hungarian motorway that connects the capital city Budapest with the Austrian border, forming part of a key international transport corridor.
  • E. M1
    M1 is a major north–south urban freeway in Johannesburg, South Africa, connecting the city center with key suburbs and routes.
  • 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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddb6fed8819090798683353a5c08 completed April 19, 2026, 1:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a035da3eacc81908b847c7ae3b45fc2 completed May 12, 2026, 5:04 p.m.
NEDg Description generation batch_6a036083e0f88190b7065f5de80f259e completed May 12, 2026, 5:16 p.m.
NED2 Entity disambiguation (via description) batch_6a0360ec1c908190a99080990793e519 completed May 12, 2026, 5:18 p.m.
Created at: April 10, 2026, 10:28 a.m.