Triple

T7069481
Position Surface form Disambiguated ID Type / Status
Subject Cesare Danova E164647 entity
Predicate spouse P13 FINISHED
Object Pamela Danova
Pamela Danova is known as the spouse of Italian-American actor Cesare Danova.
E749796 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: Pamela Danova | Statement: [Cesare Danova, spouse, Pamela Danova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pamela Danova
Context triple: [Cesare Danova, spouse, Pamela Danova]
  • A. Pamela Reeves
    Pamela Reeves was a respected American attorney and federal judge who served on the U.S. District Court for the Eastern District of Tennessee and was known for her trailblazing role as the court’s first female chief judge.
  • B. Pamela Miles
    Pamela Miles is a British actress best known for her work on stage and screen and for her long marriage to actor Tim Pigott-Smith.
  • C. Pamela Duncan
    Pamela Duncan was an American film and television actress active in the 1950s and 1960s, known for her roles in low-budget Westerns and genre pictures.
  • D. Pamela Reed
    Pamela Reed is an American actress known for her versatile character roles in film and television, including a prominent part in the comedy "Kindergarten Cop."
  • E. Pamela Brown
    Pamela Brown was a British stage and film actress known for her intense character roles in mid-20th-century cinema and theatre.
  • 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: Pamela Danova
Triple: [Cesare Danova, spouse, Pamela Danova]
Generated description
Pamela Danova is known as the spouse of Italian-American actor Cesare Danova.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pamela Danova
Target entity description: Pamela Danova is known as the spouse of Italian-American actor Cesare Danova.
  • A. Pamela Reeves
    Pamela Reeves was a respected American attorney and federal judge who served on the U.S. District Court for the Eastern District of Tennessee and was known for her trailblazing role as the court’s first female chief judge.
  • B. Pamela Miles
    Pamela Miles is a British actress best known for her work on stage and screen and for her long marriage to actor Tim Pigott-Smith.
  • C. Pamela Duncan
    Pamela Duncan was an American film and television actress active in the 1950s and 1960s, known for her roles in low-budget Westerns and genre pictures.
  • D. Pamela Reed
    Pamela Reed is an American actress known for her versatile character roles in film and television, including a prominent part in the comedy "Kindergarten Cop."
  • E. Pamela Brown
    Pamela Brown was a British stage and film actress known for her intense character roles in mid-20th-century cinema and theatre.
  • 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_69c6887b96548190a8a9b3ac8adf4119 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4aa82108190bacd5584c1c78999 completed March 27, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecc01e1b88190817a73e580cf4f03 completed April 2, 2026, 8:05 p.m.
NEDg Description generation batch_69ced05d98e481909607fd51883cd123 completed April 2, 2026, 8:23 p.m.
NED2 Entity disambiguation (via description) batch_69ced0e42edc8190af4fa07942d00e6b completed April 2, 2026, 8:26 p.m.
Created at: March 27, 2026, 2:39 p.m.