Triple

T20618378
Position Surface form Disambiguated ID Type / Status
Subject Lots Road Power Station E506626 entity
Predicate connectedTo P37 FINISHED
Object Circle line NE NERFINISHED

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: Circle line | Statement: [Lots Road Power Station, connectedTo, Circle line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Circle line
Context triple: [Lots Road Power Station, connectedTo, Circle line]
  • A. Circle line chosen
    The Circle line is a central London Underground route forming a loop through key districts and interchanges in the city’s transport network.
  • B. Circle Line
    Circle Line is the alternative name for Seoul Subway Line 2, a major loop line encircling central Seoul and serving as one of the city's busiest metro routes.
  • C. Circle Line
    Circle Line is a mass rapid transit line in Singapore that forms a loop connecting key residential, commercial, and educational districts around the city.
  • D. Circular line
    The Circular line is a driverless rapid transit line in the Taipei Metro system that forms a loop connecting multiple districts around the city.
  • E. Circular line
    Circular line is the nickname for Line 6 of the Madrid Metro, a heavily used underground route that forms a loop around central Madrid.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abdf9d7c8190969247a4ae55b781 completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:41 a.m.