Triple

T15429069
Position Surface form Disambiguated ID Type / Status
Subject Milan Metro Line 3 E369587 entity
Predicate shortName P43 FINISHED
Object M3
M3 is the third line of the Milan Metro system, running in a north–south direction and serving key areas of Milan, Italy.
E1156273 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: M3 | Statement: [Milan Metro Line 3, shortName, M3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M3
Context triple: [Milan Metro Line 3, shortName, M3]
  • A. M3
    M3 is a major motorway in the United Kingdom that connects London to Southampton, serving as a key route through southern England.
  • B. M3
    M3 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s lake or waterways.
  • C. M3
    M3 is one of the main lines of the Bucharest Metro rapid transit system, serving key residential and commercial areas of Romania’s capital.
  • D. M3
    M3 is a NASA-designed imaging spectrometer that flew on India's Chandrayaan-1 lunar mission to map the Moon’s surface mineralogy and detect water and hydroxyl signatures.
  • E. M3
    M3 is the third line of the Budapest Metro system, running in a north–south direction and serving as one of the city’s main rapid transit corridors.
  • 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: M3
Triple: [Milan Metro Line 3, shortName, M3]
Generated description
M3 is the third line of the Milan Metro system, running in a north–south direction and serving key areas of Milan, Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: M3
Target entity description: M3 is the third line of the Milan Metro system, running in a north–south direction and serving key areas of Milan, Italy.
  • A. M3
    M3 is the third line of the Budapest Metro system, running in a north–south direction and serving as one of the city’s main rapid transit corridors.
  • B. M3
    M3 is one of the main lines of the Bucharest Metro rapid transit system, serving key residential and commercial areas of Romania’s capital.
  • C. M3
    M3 is a circular line of the Copenhagen Metro that loops around the city center, connecting key districts and interchange stations.
  • D. M3
    M3 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s lake or waterways.
  • E. M3
    M3 is a major motorway in the United Kingdom that connects London to Southampton, serving as a key route through southern England.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ec31f4881908b26ff7c381d7bc9 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a827d9081909fabc48bc685ba5b completed May 9, 2026, 11:29 a.m.
NEDg Description generation batch_69ff1b4c13e08190b2ccee59da02d0ae completed May 9, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_69ff1bdb39b481908f0b1df595837bc4 completed May 9, 2026, 11:34 a.m.
Created at: April 10, 2026, 3:21 a.m.