Triple

T11893888
Position Surface form Disambiguated ID Type / Status
Subject Line 2–Green E282986 entity
Predicate connectsWith P37 FINISHED
Object Line 5–Lilac E282988 NE FINISHED

How this triple was built (2 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: Line 5–Lilac | Statement: [Line 2–Green, connectsWith, Line 5–Lilac]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5–Lilac
Context triple: [Line 2–Green, connectsWith, Line 5–Lilac]
  • A. Line 5–Lilac chosen
    Line 5–Lilac is a rapid transit line of the São Paulo Metro system serving the city’s south and southwest zones.
  • B. Metro Line 54
    Metro Line 54 is a rapid transit line in the Amsterdam Metro system that connects the city center with southeastern suburbs such as Bijlmermeer.
  • C. Line 4B
    Line 4B is a planned rapid transit line of the Ho Chi Minh City Metro intended to expand urban rail connectivity within Vietnam’s largest city.
  • D. Metro Line 5
    Metro Line 5 is a rapid transit route within a city's metro system that connects with Metro Line 6 at one or more interchange stations.
  • E. Line 4–Yellow
    Line 4–Yellow is a major driverless metro line in São Paulo’s rapid transit system, connecting key central and western districts with high-capacity, automated service.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1172988190a2c13d37220f2f93 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4180569ac81909137d56374e800c0 completed May 1, 2026, 3:03 a.m.
Created at: April 8, 2026, 9:44 p.m.