Triple

T21584656
Position Surface form Disambiguated ID Type / Status
Subject Mapo District E532616 entity
Predicate borderedBy P224 FINISHED
Object Goyang 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: Goyang | Statement: [Mapo District, borderedBy, Goyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Goyang
Context triple: [Mapo District, borderedBy, Goyang]
  • A. Goyang chosen
    Goyang is a major satellite city northwest of Seoul in South Korea, known for its rapid urban development, residential districts, and cultural attractions such as Ilsan Lake Park and KINTEX.
  • B. Gwanchang
    Gwanchang was a famed young Hwarang warrior of the Silla kingdom in ancient Korea, celebrated for his exceptional bravery and loyalty in battle.
  • C. Ga-yeong
    Ga-yeong is a Korean feminine given name that can be borne by various real or fictional individuals.
  • D. Dongmyeong
    Dongmyeong is another name for Jumong, the legendary founder and first king of the ancient Korean kingdom of Goguryeo.
  • E. Honam
    Honam is a southwestern region of South Korea known for its rich agricultural land, distinct cultural traditions, and major cities like Gwangju and Jeonju.
  • 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_69e0c4618bec8190bcb0feb74568cbb1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb5f2cc0819095552de70eb2ad8d completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.