Triple

T13071999
Position Surface form Disambiguated ID Type / Status
Subject No Reservations E329479 entity
Predicate screenwriter P2831 FINISHED
Object Carol Fuchs
Carol Fuchs is an American screenwriter best known for her work on romantic comedies, including the film "No Reservations."
E1047538 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: Carol Fuchs | Statement: [No Reservations, screenwriter, Carol Fuchs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carol Fuchs
Context triple: [No Reservations, screenwriter, Carol Fuchs]
  • A. Barbara Fuchs
    Barbara Fuchs is a literary scholar known for her work on early modern Spanish and English literature, translation, and cultural exchange.
  • B. Elisabeth Fuchs
    Elisabeth Fuchs is an Austrian conductor known for her work with orchestras and choirs, particularly in Salzburg.
  • C. Elizabeth Hofmann
    Elizabeth Hofmann is known as the spouse of American glass artist and sculptor Dan Dailey.
  • D. Anna Friedlander
    Anna Friedlander is known as the daughter of influential American photographer Lee Friedlander.
  • E. Susan Anspach
    Susan Anspach was an American actress best known for her roles in influential 1970s films such as "Five Easy Pieces" and "Blume in Love," where she often portrayed complex, independent women.
  • 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: Carol Fuchs
Triple: [No Reservations, screenwriter, Carol Fuchs]
Generated description
Carol Fuchs is an American screenwriter best known for her work on romantic comedies, including the film "No Reservations."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Carol Fuchs
Target entity description: Carol Fuchs is an American screenwriter best known for her work on romantic comedies, including the film "No Reservations."
  • A. Barbara Fuchs
    Barbara Fuchs is a literary scholar known for her work on early modern Spanish and English literature, translation, and cultural exchange.
  • B. Elisabeth Fuchs
    Elisabeth Fuchs is an Austrian conductor known for her work with orchestras and choirs, particularly in Salzburg.
  • C. Elizabeth Hofmann
    Elizabeth Hofmann is known as the spouse of American glass artist and sculptor Dan Dailey.
  • D. Anna Friedlander
    Anna Friedlander is known as the daughter of influential American photographer Lee Friedlander.
  • E. Susan Anspach
    Susan Anspach was an American actress best known for her roles in influential 1970s films such as "Five Easy Pieces" and "Blume in Love," where she often portrayed complex, independent women.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980ee6130819095d835e7ff6a8c5b completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d7cfe24819096e8f4cd496a6fd7 completed May 3, 2026, 2:36 p.m.
NEDg Description generation batch_69f7614fbe8c8190b4a32b129c64d6b0 completed May 3, 2026, 2:53 p.m.
NED2 Entity disambiguation (via description) batch_69f761a9e7448190835cfff6a1ad6405 completed May 3, 2026, 2:54 p.m.
Created at: April 9, 2026, 9 p.m.