Triple

T641266
Position Surface form Disambiguated ID Type / Status
Subject Academy Award for Best Documentary Feature E16743 entity
Predicate notableWinner P2766 FINISHED
Object Amy
Amy is a critically acclaimed 2015 documentary film about the life and career of British singer-songwriter Amy Winehouse.
 E115139 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: Amy | Statement: [Academy Award for Best Documentary Feature, notableWinner, Amy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Amy
Context triple: [Academy Award for Best Documentary Feature, notableWinner, Amy]
  • A. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • B. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • C. Anna
    Anna is a central female character in the comedy Western film "A Million Ways to Die in the West," portrayed as a sharp-shooting, quick-witted woman who helps the protagonist toughen up in the dangerous frontier.
  • D. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • E. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • 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: Amy
Triple: [Academy Award for Best Documentary Feature, notableWinner, Amy]
Generated description
Amy is a critically acclaimed 2015 documentary film about the life and career of British singer-songwriter Amy Winehouse.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Amy
Target entity description: Amy is a critically acclaimed 2015 documentary film about the life and career of British singer-songwriter Amy Winehouse.
  • A. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • B. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • C. Anna
    Anna is a central female character in the comedy Western film "A Million Ways to Die in the West," portrayed as a sharp-shooting, quick-witted woman who helps the protagonist toughen up in the dangerous frontier.
  • D. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • E. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • 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_69a4936be1c88190af56540324b57da7 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49f02bc2c8190b8a92b2505768c19 completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16f129a48190aac137cd96e7f515 completed March 7, 2026, 12:15 p.m.
NEDg Description generation batch_69ac182a38e88190ab40afbe22ac2207 completed March 7, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_69ac18bde2b08190bcf62b780b61052c completed March 7, 2026, 12:23 p.m.
Created at: March 1, 2026, 7:36 p.m.