Triple

T2899180
Position Surface form Disambiguated ID Type / Status
Subject Ginnifer Goodwin E62614 entity
Predicate givenName P17 FINISHED
Object Ginnifer
Ginnifer is the distinctive first name of American actress Ginnifer Goodwin, known for roles in projects like "Once Upon a Time" and "Big Love."
E310691 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: Ginnifer | Statement: [Ginnifer Goodwin, givenName, Ginnifer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ginnifer
Context triple: [Ginnifer Goodwin, givenName, Ginnifer]
  • A. Gina
    Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
  • B. Ginjer Buchanan
    Ginjer Buchanan is an American science fiction and fantasy editor best known for her influential work at Ace Books and for winning the Hugo Award for Best Editor, Long Form.
  • C. Greer Shephard
    Greer Shephard is an American television producer and director best known for co-creating and producing acclaimed drama series such as Nip/Tuck and The Closer.
  • D. Rebecca Calhoun
    Rebecca Calhoun was the wife of American Revolutionary War general and South Carolina politician Andrew Pickens.
  • E. Gillian
    Gillian is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • 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: Ginnifer
Triple: [Ginnifer Goodwin, givenName, Ginnifer]
Generated description
Ginnifer is the distinctive first name of American actress Ginnifer Goodwin, known for roles in projects like "Once Upon a Time" and "Big Love."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ginnifer
Target entity description: Ginnifer is the distinctive first name of American actress Ginnifer Goodwin, known for roles in projects like "Once Upon a Time" and "Big Love."
  • A. Gina
    Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
  • B. Ginjer Buchanan
    Ginjer Buchanan is an American science fiction and fantasy editor best known for her influential work at Ace Books and for winning the Hugo Award for Best Editor, Long Form.
  • C. Greer Shephard
    Greer Shephard is an American television producer and director best known for co-creating and producing acclaimed drama series such as Nip/Tuck and The Closer.
  • D. Rebecca Calhoun
    Rebecca Calhoun was the wife of American Revolutionary War general and South Carolina politician Andrew Pickens.
  • E. Gillian
    Gillian is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0ad7bbc8190822738baa6935b74 completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b055fe13448190bf25832219fd5f0c completed March 10, 2026, 5:33 p.m.
NEDg Description generation batch_69b062e280448190a494b6d3c119de7f completed March 10, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_69b0633ee82c8190822a4b25a936add9 completed March 10, 2026, 6:30 p.m.
Created at: March 6, 2026, 10:10 p.m.