Triple

T13996610
Position Surface form Disambiguated ID Type / Status
Subject The Boy Who Knew Too Much E336713 entity
Predicate hasPart P35 FINISHED
Object Rain E497232 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: Rain | Statement: [The Boy Who Knew Too Much, hasPart, Rain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rain
Context triple: [The Boy Who Knew Too Much, hasPart, Rain]
  • A. Rain
    Rain is a surname shared by various individuals, including those in the entertainment industry such as actress and writer Jeramie Rain.
  • B. Rain
    "Rain" is a 2001 New Zealand drama film directed by Christine Jeffs, adapted from Kirsty Gunn’s novel about a young girl’s turbulent coming-of-age during a tense family holiday.
  • C. Rain
    "Rain" is a 1932 American pre-Code drama film starring Walter Huston, based on W. Somerset Maugham’s short story about moral conflict and temptation in the South Seas.
  • D. Rain
    Rain is a South Korean singer and actor known internationally for his music career and roles in films and television dramas.
  • E. Rain chosen
    "Rain" is a 1921 short story by W. Somerset Maugham, renowned for its intense psychological drama set in the South Pacific and its exploration of morality, sexuality, and religious hypocrisy.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2eb68ba88190bfaf10777d607bf3 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0934b74819094ec7309c23a3e2a completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:19 p.m.