Triple

T17000749
Position Surface form Disambiguated ID Type / Status
Subject Choi Woo-shik E412434 entity
Predicate appearedIn P795 FINISHED
Object Hogu’s Love E1245267 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: Hogu’s Love | Statement: [Choi Woo-shik, appearedIn, Hogu’s Love]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hogu’s Love
Context triple: [Choi Woo-shik, appearedIn, Hogu’s Love]
  • A. Hogu’s Love chosen
    Hogu’s Love is a South Korean romantic comedy television drama that follows a sweet but naive young man entangled in an unexpected romance and personal growth.
  • B. Baddo Love
    Baddo Love is a track from Olamide’s influential Nigerian hip-hop album *Baddest Guy Ever Liveth*.
  • C. The Hoose-Gow
    The Hoose-Gow is a 1929 Laurel and Hardy short comedy film known for its prison-escape antics and slapstick humor.
  • D. My Lovely Sam Soon
    My Lovely Sam Soon is a popular South Korean romantic comedy television drama centered on a pastry chef navigating love, career, and self-acceptance.
  • E. Tales of Burning Love
    Tales of Burning Love is a novel by Louise Erdrich that interweaves the lives and stories of several women connected by their relationships with the same charismatic man, exploring themes of love, loss, and identity.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d37d9f9081909aef52426d88940d completed April 18, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b451ff88190b63f4ebddf93f153 completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 5:32 a.m.