Triple

T106803
Position Surface form Disambiguated ID Type / Status
Subject Academy Award E2155 entity
Predicate alsoKnownAs P39 FINISHED
Object Oscar
The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
 E11086 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: Oscar | Statement: [Academy Award, alsoKnownAs, Oscar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oscar
Context triple: [Academy Award, alsoKnownAs, Oscar]
  • A. Garland
    Garland is a large suburban city in the Dallas–Fort Worth metropolitan area known for its diverse community and mixed residential, commercial, and industrial character.
  • B. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • C. Hancock
    Hancock is a prominent surname most famously associated with John Hancock, a key figure of the American Revolution and first signer of the United States Declaration of Independence.
  • D. Harold
    Harold is a masculine given name of Old English origin, historically borne by several notable figures including kings and modern public personalities.
  • E. Timothy
    Timothy is the given first name of Sir Tim Berners-Lee, the British computer scientist who invented the World Wide Web.
  • 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: Oscar
Triple: [Academy Award, alsoKnownAs, Oscar]
Generated description
The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oscar
Target entity description: The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
  • A. Garland
    Garland is a large suburban city in the Dallas–Fort Worth metropolitan area known for its diverse community and mixed residential, commercial, and industrial character.
  • B. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • C. Hancock
    Hancock is a prominent surname most famously associated with John Hancock, a key figure of the American Revolution and first signer of the United States Declaration of Independence.
  • D. Harold
    Harold is a masculine given name of Old English origin, historically borne by several notable figures including kings and modern public personalities.
  • E. Timothy
    Timothy is the given first name of Sir Tim Berners-Lee, the British computer scientist who invented the World Wide Web.
  • 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_69a24e0a5b7c81908d52da08c60dabc4 completed Feb. 28, 2026, 2:08 a.m.
NER Named-entity recognition batch_69a256cac6d4819083b50c9c9d95e975 completed Feb. 28, 2026, 2:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69a275e644a48190aa2b8cb142b14394 completed Feb. 28, 2026, 4:58 a.m.
NEDg Description generation batch_69a276cddee08190aab0959702d44f67 completed Feb. 28, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_69a277b7aee8819085cb05afc213eaff completed Feb. 28, 2026, 5:05 a.m.
Created at: Feb. 28, 2026, 2:12 a.m.