Triple

T14888350
Position Surface form Disambiguated ID Type / Status
Subject Budapest Metro Line 3 E359687 entity
Predicate alsoKnownAs P39 FINISHED
Object 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.
 E1126165 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: [Budapest Metro Line 3, alsoKnownAs, M3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M3
Context triple: [Budapest Metro Line 3, alsoKnownAs, 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 a circular line of the Copenhagen Metro that loops around the city center, connecting key districts and interchange stations.
  • 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: [Budapest Metro Line 3, alsoKnownAs, M3]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M3
Target entity description: 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.
  • 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 a circular line of the Copenhagen Metro that loops around the city center, connecting key districts and interchange stations.
  • D. 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.
  • E. 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.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded5f6cf5c8190b6b28f58fafe5d59 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b5f22c08190a9530cbd78cfc801 completed May 8, 2026, 11:01 p.m.
NEDg Description generation batch_69fe6f9b33748190aee0c27879866ca1 completed May 8, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_69fe703e8c28819081b7bfe638a2202e completed May 8, 2026, 11:22 p.m.
Created at: April 10, 2026, 2:08 a.m.