Triple

T22398864
Position Surface form Disambiguated ID Type / Status
Subject Battle of Daecheong E553704 entity
Predicate nearIsland P19486 FINISHED
Object Daecheongdo 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: Daecheongdo | Statement: [Battle of Daecheong, nearIsland, Daecheongdo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daecheongdo
Context triple: [Battle of Daecheong, nearIsland, Daecheongdo]
  • A. Daecheongdo chosen
    Daecheongdo is a South Korean island in the Yellow Sea known for its strategic location near the maritime border with North Korea and its role in regional security and fishing.
  • B. Ryanggang-do
    Ryanggang-do is a mountainous inland province in northern North Korea, known for containing Mount Paektu and bordering China along the upper Yalu River.
  • C. Dobongsan
    Dobongsan is a prominent, rocky mountain in northern South Korea known for its scenic hiking trails, granite peaks, and location within Bukhansan National Park.
  • D. Ok-dong
    Ok-dong is a neighborhood in Ulsan, South Korea, known for encompassing the large urban green space of Ulsan Grand Park.
  • E. Gyeryongsan
    Gyeryongsan is a prominent mountain in central South Korea known for its scenic national park, rich biodiversity, and cultural sites including historic Buddhist temples.
  • 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_69e11e4da7048190b4387d422a9a0de5 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15861ac248190a967f534feea0265 completed April 29, 2026, 1:01 a.m.
Created at: April 16, 2026, 8:46 p.m.