Triple

T16849225
Position Surface form Disambiguated ID Type / Status
Subject The Autobiography E409625 entity
Predicate hasPart P35 FINISHED
Object Wings
"Wings" is a section of The Autobiography that focuses on a distinct phase or theme in the subject’s life, often emphasizing growth, freedom, or transformation.
 E1236695 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: Wings | Statement: [The Autobiography, hasPart, Wings]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wings
Context triple: [The Autobiography, hasPart, Wings]
  • A. Wings
    Wings is an American sitcom that aired in the 1990s, centered on the lives and misadventures of staff at a small regional airline on Nantucket Island.
  • B. Wings
    "Wings" is a track from the Black Eyed Peas' concept album *Masters of the Sun Vol. 1*, blending hip hop with socially conscious themes.
  • C. Wings
    Wings is a 1927 silent World War I aviation film that became the first movie ever to win the Academy Award for Best Picture.
  • D. Wings
    Wings is a 1966 Soviet drama film directed by Larisa Shepitko that explores the postwar life and inner struggles of a former World War II fighter pilot turned school principal.
  • E. Wings
    Wings is a smokeless tobacco brand produced by the American Snuff Company.
  • 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: Wings
Triple: [The Autobiography, hasPart, Wings]
Generated description
"Wings" is a section of The Autobiography that focuses on a distinct phase or theme in the subject’s life, often emphasizing growth, freedom, or transformation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wings
Target entity description: "Wings" is a section of The Autobiography that focuses on a distinct phase or theme in the subject’s life, often emphasizing growth, freedom, or transformation.
  • A. Wings
    "Wings" is a track from the Black Eyed Peas' concept album *Masters of the Sun Vol. 1*, blending hip hop with socially conscious themes.
  • B. Wings
    "Wings" is an upbeat pop anthem by British girl group Little Mix that promotes self-confidence and empowerment.
  • C. Wings
    "Wings" is a pop song by Australian singer-songwriter Delta Goodrem, known for its uplifting lyrics and powerful vocal performance.
  • D. Wings
    Wings is a music production entity known for working on the track "Letting Go."
  • E. Wings
    "Wings" is a folk-rock song by the Stone Poneys, best known for featuring Linda Ronstadt’s early vocals and helping launch her career.
  • 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_69d883952b048190887740a980b712ed completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b377b5d881909f0878dd9957f3bc completed April 18, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb1f02648190937c692af83843dc completed May 10, 2026, 5:06 p.m.
NEDg Description generation batch_6a00bbc80d54819092de4ee363508b49 completed May 10, 2026, 5:09 p.m.
NED2 Entity disambiguation (via description) batch_6a00bc633abc8190a86808986ba294ec completed May 10, 2026, 5:12 p.m.
Created at: April 10, 2026, 5:24 a.m.