Triple

T19701902
Position Surface form Disambiguated ID Type / Status
Subject Paju, Gyeonggi Province E473117 entity
Predicate hasLandmark P105 FINISHED
Object Dorasan Station 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: Dorasan Station | Statement: [Paju, Gyeonggi Province, hasLandmark, Dorasan Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dorasan Station
Context triple: [Paju, Gyeonggi Province, hasLandmark, Dorasan Station]
  • A. Dorasan Station chosen
    Dorasan Station is a symbolic railway station in South Korea near the Demilitarized Zone, built as a hopeful future gateway for rail travel and trade between South and North Korea.
  • B. Sasang Station
    Sasang Station is a major railway and subway interchange in Busan, South Korea, serving as a key transit hub for both local and intercity travel.
  • C. Jang Bogo Station
    Jang Bogo Station is a South Korean Antarctic research base located on the Scott Coast of Victoria Land, supporting studies in fields such as climate science, glaciology, and marine biology.
  • D. Sindorim Station
    Sindorim Station is a major transfer hub in southwestern Seoul where multiple subway lines and extensive commercial facilities converge.
  • E. Sajik Station
    Sajik Station is a subway station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e642b667908190841bb5fb7bfdb3f7 completed April 20, 2026, 3:13 p.m.
Created at: April 10, 2026, 1:46 p.m.