Triple

T11894013
Position Surface form Disambiguated ID Type / Status
Subject Line 15–Silver E282989 entity
Predicate connectsWith P37 FINISHED
Object Line 2–Green E282986 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 2–Green | Statement: [Line 15–Silver, connectsWith, Line 2–Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2–Green
Context triple: [Line 15–Silver, connectsWith, Line 2–Green]
  • A. Line 2–Green chosen
    Line 2–Green is a major rapid transit line of the São Paulo Metro system, serving key central and eastern districts of São Paulo, Brazil.
  • B. Line 2 (Blue Line)
    Line 2 (Blue Line) is one of the main lines of the Mexico City Metro system, running on a north–south axis through several key central and residential areas.
  • C. Line 3–Red
    Line 3–Red is one of the busiest and most important lines of the São Paulo Metro, running east–west across the city and connecting key residential and commercial areas.
  • D. LRT Line 2
    LRT Line 2 is an elevated rapid transit line in Metro Manila, Philippines, running east–west and serving major areas including Quezon City, Manila, and Pasig.
  • E. Metro Line 3
    Metro Line 3 is a major Mexico City Metro route that runs north–south across the city, connecting key residential and commercial areas including the Gustavo A. Madero borough.
  • 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_69f4586898888190b58e3102d7edf7df completed May 1, 2026, 7:38 a.m.
Created at: April 8, 2026, 9:44 p.m.