Triple

T3220434
Position Surface form Disambiguated ID Type / Status
Subject Copenhagen Metro E67498 entity
Predicate hasLine P35 FINISHED
Object 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.
 E338237 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: [Copenhagen Metro, hasLine, M1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M1
Context triple: [Copenhagen Metro, hasLine, M1]
  • A. M1
    M1 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s waters.
  • B. M1
    M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
  • C. M11
    M11 is a major motorway in England that connects London to Cambridge and the East Anglia region.
  • D. MI1
    MI1 was an early British military intelligence section responsible for handling secret information and code-related work before later intelligence agencies were formally established.
  • E. M16
    M16 is the Osaka Metro station code assigned to Umeda Station on the Midosuji Line in Osaka, Japan.
  • 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: [Copenhagen Metro, hasLine, M1]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M1
Target entity description: 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.
  • A. M1
    M1 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s waters.
  • B. M1
    M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
  • C. M11
    M11 is a major motorway in England that connects London to Cambridge and the East Anglia region.
  • D. MI1
    MI1 was an early British military intelligence section responsible for handling secret information and code-related work before later intelligence agencies were formally established.
  • E. M16
    M16 is the Osaka Metro station code assigned to Umeda Station on the Midosuji Line in Osaka, Japan.
  • 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_69ad858b8adc8190ad989712c87a476b completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adae16f20081909d7f3bac016f961d completed March 8, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2624a770881908f0a9415b6f74ee0 completed March 12, 2026, 6:50 a.m.
NEDg Description generation batch_69b2662274988190ae62791744df0562 completed March 12, 2026, 7:07 a.m.
NED2 Entity disambiguation (via description) batch_69b266bf6bf48190a4480bf9a699dae8 completed March 12, 2026, 7:09 a.m.
Created at: March 8, 2026, 3:08 p.m.