Triple

T18412073
Position Surface form Disambiguated ID Type / Status
Subject Milan Metro Line 1 E441782 entity
Predicate alsoKnownAs P39 FINISHED
Object M1
M1 is the first line of the Milan Metro system, a major rapid transit route serving the Italian city of Milan.
 E1322747 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: [Milan Metro Line 1, alsoKnownAs, M1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M1
Context triple: [Milan Metro Line 1, alsoKnownAs, 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: [Milan Metro Line 1, alsoKnownAs, M1]
Generated description
M1 is the first line of the Milan Metro system, a major rapid transit route serving the Italian city of Milan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M1
Target entity description: M1 is the first line of the Milan Metro system, a major rapid transit route serving the Italian city of Milan.
  • 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 Bucharest Metro, forming part of the city’s core rapid transit network.
  • 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 one of the main lines of the Copenhagen Metro, providing rapid transit service through central Copenhagen and connecting key residential and commercial areas.
  • E. M1
    M1 is a light metro line in Lausanne, Switzerland, connecting the city center with the university and lakeside areas.
  • 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51a24e130819082b92f98d8d5fa3c completed April 19, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03e24be008819083d4ab019e8c66a6 completed May 13, 2026, 2:30 a.m.
NEDg Description generation batch_6a03e7a576b881908267669e3ed394cf completed May 13, 2026, 2:53 a.m.
NED2 Entity disambiguation (via description) batch_6a03e8046c188190b860addd21ee8346 completed May 13, 2026, 2:55 a.m.
Created at: April 10, 2026, 10:47 a.m.