Triple

T16928401
Position Surface form Disambiguated ID Type / Status
Subject Yongin E410636 entity
Predicate isConnectedBy P845 FINISHED
Object EverLine E467939 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: EverLine | Statement: [Yongin, isConnectedBy, EverLine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EverLine
Context triple: [Yongin, isConnectedBy, EverLine]
  • A. EverLine chosen
    EverLine is an automated light rail transit line serving the city of Yongin in the Seoul Capital Area, connecting local districts to the broader Seoul Metropolitan Subway network.
  • B. Evergreen Line
    Evergreen Line is a major Taiwanese container shipping company known for operating a large global fleet and extensive international trade routes.
  • C. City Line
    City Line is a suburban railway route serving various districts within Cardiff, Wales, as part of the local commuter rail network.
  • D. City Line
    City Line is a residential neighborhood in eastern Brooklyn, New York City, located near the borough’s border with Queens.
  • E. City Line
    City Line is a commuter rail service on Bangkok’s Suvarnabhumi Airport Rail Link that connects the airport with central city stations using frequent, all-stop trains.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cdf3fc3c8190a884f7ecd5c47adb completed April 18, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfdb6b608190af910e225d942d37 completed May 10, 2026, 6:35 p.m.
Created at: April 10, 2026, 5:30 a.m.