Triple

T2220126
Position Surface form Disambiguated ID Type / Status
Subject Drunk in Love E48120 entity
Predicate producer P490 FINISHED
Object Detail
Detail is an American record producer and songwriter known for crafting hit R&B and hip-hop tracks for major artists such as Beyoncé and Lil Wayne.
 E245935 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: Detail | Statement: [Drunk in Love, producer, Detail]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Detail
Context triple: [Drunk in Love, producer, Detail]
  • A. Dim
    Dim is the large but gentle rhinoceros beetle who performs as a circus "strongman" in Pixar's animated film *A Bug's Life*.
  • B. DED
    DED is the commonly used abbreviation for the ASME Design Engineering Division, a professional group within ASME focused on advancing the field of mechanical design engineering.
  • C. Spare
    Spare is Prince Harry, Duke of Sussex’s candid memoir detailing his life within the British royal family and his personal struggles and experiences.
  • D. DESE
    DESE is the state agency responsible for overseeing public elementary and secondary education in Massachusetts, including standards, accountability, and school support.
  • E. DET
    DET is the standard NHL abbreviation for the Detroit Red Wings professional ice hockey team.
  • 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: Detail
Triple: [Drunk in Love, producer, Detail]
Generated description
Detail is an American record producer and songwriter known for crafting hit R&B and hip-hop tracks for major artists such as Beyoncé and Lil Wayne.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Detail
Target entity description: Detail is an American record producer and songwriter known for crafting hit R&B and hip-hop tracks for major artists such as Beyoncé and Lil Wayne.
  • A. Dim
    Dim is the large but gentle rhinoceros beetle who performs as a circus "strongman" in Pixar's animated film *A Bug's Life*.
  • B. DED
    DED is the commonly used abbreviation for the ASME Design Engineering Division, a professional group within ASME focused on advancing the field of mechanical design engineering.
  • C. Spare
    Spare is Prince Harry, Duke of Sussex’s candid memoir detailing his life within the British royal family and his personal struggles and experiences.
  • D. DESE
    DESE is the state agency responsible for overseeing public elementary and secondary education in Massachusetts, including standards, accountability, and school support.
  • E. DET
    DET is the standard NHL abbreviation for the Detroit Red Wings professional ice hockey team.
  • 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_69a88aa1ee708190862c8c378c41e9eb completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc01386588190a9507f2969a201ca completed March 7, 2026, 6:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae655df21c8190aa9624f15955c565 completed March 9, 2026, 6:14 a.m.
NEDg Description generation batch_69ae667dede88190b3d1f8bb8866e19e completed March 9, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae66f12c648190a146de7b2bfdb541 completed March 9, 2026, 6:21 a.m.
Created at: March 4, 2026, 7:46 p.m.