Triple

T8036439
Position Surface form Disambiguated ID Type / Status
Subject Lizzy Caplan E187119 entity
Predicate familyName P18 FINISHED
Object Caplan
Caplan is a surname most notably associated with American actress Lizzy Caplan, known for her roles in film and television.
 E708548 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: Caplan | Statement: [Lizzy Caplan, familyName, Caplan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Caplan
Context triple: [Lizzy Caplan, familyName, Caplan]
  • A. Parnes
    Parnes is a mountain in Greece traditionally associated with the ancient Greek personifications of mountains known as the Ourea.
  • B. Nissalke
    Nissalke is the surname of Tom Nissalke, an American professional basketball coach known for his stints in the NBA and ABA.
  • C. Asplund
    Asplund is a Swedish surname most notably associated with architect Gunnar Asplund, a key figure in Nordic Classicism and early modernist architecture.
  • D. Kleiman
    Kleiman is a surname of Dutch origin borne by various notable individuals, including those associated with the Dutch resistance during World War II.
  • E. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • 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: Caplan
Triple: [Lizzy Caplan, familyName, Caplan]
Generated description
Caplan is a surname most notably associated with American actress Lizzy Caplan, known for her roles in film and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Caplan
Target entity description: Caplan is a surname most notably associated with American actress Lizzy Caplan, known for her roles in film and television.
  • A. Parnes
    Parnes is a mountain in Greece traditionally associated with the ancient Greek personifications of mountains known as the Ourea.
  • B. Nissalke
    Nissalke is the surname of Tom Nissalke, an American professional basketball coach known for his stints in the NBA and ABA.
  • C. Asplund
    Asplund is a Swedish surname most notably associated with architect Gunnar Asplund, a key figure in Nordic Classicism and early modernist architecture.
  • D. Kleiman
    Kleiman is a surname of Dutch origin borne by various notable individuals, including those associated with the Dutch resistance during World War II.
  • E. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • 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_69ca82ae2d1081909dbfee42b41db419 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f188e1c8190b92760c91d31f2df completed March 31, 2026, 3:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56fa97ac8190a0bd646d9ec345e4 completed March 31, 2026, 11:21 p.m.
NEDg Description generation batch_69cc58abd96c8190ab9eeaece67d5408 completed March 31, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cc2f71081909cb7c0c245368edb completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:22 p.m.