Triple

T13996633
Position Surface form Disambiguated ID Type / Status
Subject The Boy Who Knew Too Much E336713 entity
Predicate notableSingle P3283 FINISHED
Object Rain
"Rain" is a popular song by South Korean singer Rain, showcasing his R&B-influenced K-pop style and helping solidify his status as a leading solo artist in Asia.
E387856 NE FINISHED

How this triple was built (4 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, notableSingle, Rain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rain
Context triple: [The Boy Who Knew Too Much, notableSingle, 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 form of precipitation in which liquid water droplets fall from clouds to the Earth's surface.
  • 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 soulful R&B song by American singer-songwriter Ant Clemons that showcases his emotive vocals and introspective lyricism.
  • E. Rain
    "Rain" is a track from Kanye West's gospel-influenced album *Jesus Is Born*, performed by the Sunday Service Choir.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rain
Triple: [The Boy Who Knew Too Much, notableSingle, Rain]
Generated description
"Rain" is a popular song by South Korean singer Rain, showcasing his R&B-influenced K-pop style and helping solidify his status as a leading solo artist in Asia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rain
Target entity description: "Rain" is a popular song by South Korean singer Rain, showcasing his R&B-influenced K-pop style and helping solidify his status as a leading solo artist in Asia.
  • A. Rain chosen
    Rain is a South Korean singer and actor known internationally for his music career and roles in films and television dramas.
  • B. Rain
    "Rain" is a song by Canadian singer-songwriter Jessie Reyez, known for its emotive vocals and introspective lyrics.
  • C. Rain
    "Rain" is a soulful R&B song by American singer-songwriter Ant Clemons that showcases his emotive vocals and introspective lyricism.
  • D. Rain
    "Rain" is a song by British singer-songwriter Michael Holbrook Penniman Jr., better known as Mika, showcasing his signature pop style and theatrical vocals.
  • E. Rain
    "Rain" is a song by the American rock band Empress.
  • F. None of above.

Provenance (5 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_69fcdef5e0648190ace4ec1605968e30 completed May 7, 2026, 6:50 p.m.
NEDg Description generation batch_69fcdfd372e0819089f0b48f84a63ab4 completed May 7, 2026, 6:54 p.m.
NED2 Entity disambiguation (via description) batch_69fce027c628819085738433b5d5525d completed May 7, 2026, 6:55 p.m.
Created at: April 9, 2026, 10:19 p.m.