Triple

T11845361
Position Surface form Disambiguated ID Type / Status
Subject NoMad E281759 entity
Predicate adjacentTo P224 FINISHED
Object Koreatown E3070 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: Koreatown | Statement: [NoMad, adjacentTo, Koreatown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koreatown
Context triple: [NoMad, adjacentTo, Koreatown]
  • A. Koreatown chosen
    Koreatown is a vibrant Manhattan neighborhood known for its dense concentration of Korean restaurants, shops, and cultural businesses centered around West 32nd Street near the Empire State Building.
  • B. Koreatown
    Koreatown is a dense Los Angeles neighborhood known for its vibrant Korean-American community, late-night dining, and mix of historic and modern urban development.
  • C. Shin-Okubo Koreatown
    Shin-Okubo Koreatown is a vibrant Korean cultural and commercial district in Tokyo known for its K-pop shops, Korean restaurants, and beauty stores.
  • D. Gangnam District
    Gangnam District is a wealthy, high-end commercial and residential area in Seoul, South Korea, known for its skyscrapers, luxury shopping, and vibrant nightlife.
  • E. Koreatown, Toronto
    Koreatown, Toronto is a vibrant Toronto neighbourhood along Bloor Street West known for its concentration of Korean restaurants, shops, and cultural businesses.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65b5ff08190bb58361f6a6acdca completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f167a876048190aeeeccebae9e46ad completed April 29, 2026, 2:06 a.m.
Created at: April 8, 2026, 9:43 p.m.