Triple

T3138215
Position Surface form Disambiguated ID Type / Status
Subject Bruno Mars E65582 entity
Predicate notableSingle P3283 FINISHED
Object Marry You
"Marry You" is a catchy pop song by Bruno Mars known for its upbeat, romantic theme about impulsively getting married.
 E329501 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: Marry You | Statement: [Bruno Mars, notableSingle, Marry You]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marry You
Context triple: [Bruno Mars, notableSingle, Marry You]
  • A. Marry You
    "Marry You" is a song featured on the collaborative blues album "Riding with the King" by B.B. King and Eric Clapton.
  • B. Watch Me Get Married
    "Watch Me Get Married" is a song by Bill Callahan from his introspective 2019 album "Shepherd in a Sheepskin Vest."
  • C. Drunk in Love
    "Drunk in Love" is a sultry, trap-influenced R&B song by Beyoncé featuring Jay-Z that became one of her signature hits following its release in 2013.
  • D. Can't Stop the Feeling!
    "Can't Stop the Feeling!" is a 2016 upbeat pop song by Justin Timberlake, known for its feel-good dance vibe and association with the animated film Trolls.
  • E. Yes I Do
    "Yes I Do" is a song performed by British actress and singer Carmen Ejogo, known for her work in film, television, and music.
  • 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: Marry You
Triple: [Bruno Mars, notableSingle, Marry You]
Generated description
"Marry You" is a catchy pop song by Bruno Mars known for its upbeat, romantic theme about impulsively getting married.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marry You
Target entity description: "Marry You" is a catchy pop song by Bruno Mars known for its upbeat, romantic theme about impulsively getting married.
  • A. Marry You
    "Marry You" is a song featured on the collaborative blues album "Riding with the King" by B.B. King and Eric Clapton.
  • B. Watch Me Get Married
    "Watch Me Get Married" is a song by Bill Callahan from his introspective 2019 album "Shepherd in a Sheepskin Vest."
  • C. Drunk in Love
    "Drunk in Love" is a sultry, trap-influenced R&B song by Beyoncé featuring Jay-Z that became one of her signature hits following its release in 2013.
  • D. Can't Stop the Feeling!
    "Can't Stop the Feeling!" is a 2016 upbeat pop song by Justin Timberlake, known for its feel-good dance vibe and association with the animated film Trolls.
  • E. Yes I Do
    "Yes I Do" is a song performed by British actress and singer Carmen Ejogo, known for her work in film, television, and music.
  • F. None of above. chosen

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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada574509c81908a88bb10ea35516d completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f8a1a2081909081c36075d4ddbe completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2137b30508190a5a9a439d77ae3bb completed March 12, 2026, 1:14 a.m.
NED2 Entity disambiguation (via description) batch_69b21413338c8190997d0f2f11f41008 completed March 12, 2026, 1:17 a.m.
Created at: March 8, 2026, 3:05 p.m.