Triple

T17118641
Position Surface form Disambiguated ID Type / Status
Subject Helsinki public transport network E415404 entity
Predicate hasMetroLine P17559 FINISHED
Object M2
M2 is one of the main metro lines in Helsinki’s public transportation system, serving key districts across the city and its surrounding areas.
E1250914 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: M2 | Statement: [Helsinki public transport network, hasMetroLine, M2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M2
Context triple: [Helsinki public transport network, hasMetroLine, M2]
  • A. M2
    M2 is a major British motorway that connects London with the port town of Dover in Kent, serving as an important route to the Channel ports.
  • B. M2
    M2 was the original name of MTV2, a U.S. cable television channel that focused on music videos and youth-oriented programming.
  • C. M2
    M2 is one of the main lines of the Budapest Metro, running east–west across the city and connecting several key transport hubs.
  • D. M2
    M2 is a boat line that operates as part of Geneva’s public transport network, providing passenger services across the city’s waters.
  • E. M2
    M2 is a central Manchester, England postcode district covering part of the city’s main commercial and business area.
  • 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: M2
Triple: [Helsinki public transport network, hasMetroLine, M2]
Generated description
M2 is one of the main metro lines in Helsinki’s public transportation system, serving key districts across the city and its surrounding areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: M2
Target entity description: M2 is one of the main metro lines in Helsinki’s public transportation system, serving key districts across the city and its surrounding areas.
  • A. M2
    M2 is one of the main lines of the Copenhagen Metro, connecting central Copenhagen with key districts and the airport.
  • B. M2
    M2 is one of the main lines of the Budapest Metro, running east–west across the city and connecting several key transport hubs.
  • C. M2
    M2 is one of the main lines of the Bucharest Metro, running on a north–south axis and serving several of the city’s key residential and commercial areas.
  • D. M2
    M2 is the second line of the Warsaw Metro, running east–west across the city and connecting key districts on both sides of the Vistula River.
  • E. M2
    M2 is a metro line in Lausanne, Switzerland, forming part of the city's urban rapid transit network.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e8086a388190a655a044feccab14 completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a0e11108190bfcf858142aa9ff3 completed May 11, 2026, 2:08 a.m.
NEDg Description generation batch_6a013b749680819097159f0fdc379f2c completed May 11, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_6a013bf9ef508190aac1155680f33eaf completed May 11, 2026, 2:16 a.m.
Created at: April 10, 2026, 5:35 a.m.