Triple

T14711952
Position Surface form Disambiguated ID Type / Status
Subject The Cape E345566 entity
Predicate stars P1956 FINISHED
Object Jennifer Ferrin
Jennifer Ferrin is an American actress best known for her work in television dramas and series such as "The Cape" and "As the World Turns."
E1116240 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: Jennifer Ferrin | Statement: [The Cape, stars, Jennifer Ferrin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Ferrin
Context triple: [The Cape, stars, Jennifer Ferrin]
  • A. Emily Greer
    Emily Greer is a notable individual recognized as a prominent bearer of the surname Greer.
  • B. Teresa Nielsen Hayden
    Teresa Nielsen Hayden is an American science fiction editor, writer, and influential blogger known for her work at Tor Books and her role in online fan communities.
  • C. Elizabeth Kern
    Elizabeth Kern was the wife of renowned American jazz clarinetist and bandleader Artie Shaw.
  • D. Sandra Hunt
    Sandra Hunt is best known as the wife of legendary Los Angeles Dodgers broadcaster Vin Scully.
  • E. Jan Platt
    Jan Platt was a prominent Tampa-area public servant and longtime Hillsborough County commissioner known for her advocacy of libraries, environmental protection, and ethical government.
  • 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: Jennifer Ferrin
Triple: [The Cape, stars, Jennifer Ferrin]
Generated description
Jennifer Ferrin is an American actress best known for her work in television dramas and series such as "The Cape" and "As the World Turns."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jennifer Ferrin
Target entity description: Jennifer Ferrin is an American actress best known for her work in television dramas and series such as "The Cape" and "As the World Turns."
  • A. Emily Greer
    Emily Greer is a notable individual recognized as a prominent bearer of the surname Greer.
  • B. Teresa Nielsen Hayden
    Teresa Nielsen Hayden is an American science fiction editor, writer, and influential blogger known for her work at Tor Books and her role in online fan communities.
  • C. Elizabeth Kern
    Elizabeth Kern was the wife of renowned American jazz clarinetist and bandleader Artie Shaw.
  • D. Sandra Hunt
    Sandra Hunt is best known as the wife of legendary Los Angeles Dodgers broadcaster Vin Scully.
  • E. Jan Platt
    Jan Platt was a prominent Tampa-area public servant and longtime Hillsborough County commissioner known for her advocacy of libraries, environmental protection, and ethical government.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb982bf248190881e21a8a0861a3f completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf08f2aa08190a5ac3240d1de90fb completed May 8, 2026, 2:17 p.m.
NEDg Description generation batch_69fdf23d4928819093630e25616abb2d completed May 8, 2026, 2:25 p.m.
NED2 Entity disambiguation (via description) batch_69fdf31fcb4081908a88cf4d4c5ddced completed May 8, 2026, 2:28 p.m.
Created at: April 10, 2026, 1:28 a.m.