Triple

T22228616
Position Surface form Disambiguated ID Type / Status
Subject George F. Will E549408 entity
Predicate hasChild P369 FINISHED
Object Victoria Will
Victoria Will is an American photographer known for her distinctive celebrity portraiture and editorial work in major publications.
E542824 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: Victoria Will | Statement: [George F. Will, hasChild, Victoria Will]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria Will
Context triple: [George F. Will, hasChild, Victoria Will]
  • A. Victoria Will
    Victoria Will is an American photographer known for her distinctive celebrity portraiture and editorial work in major publications.
  • B. Victoria Grace
    Victoria Grace is an actress and voice actress known for her role in the animated series "Pacific Rim: The Black."
  • C. Victoria Prince
    Victoria Prince is an American former professional volleyball player and the wife of Kevin Federline, with whom she has twin sons.
  • D. Victoria Royal
    Victoria Royal is a central fictional member of the British monarchy in the narrative surrounding The Royal Family.
  • E. Victoria Elizabeth Bateman
    Victoria Elizabeth Bateman is the mother of American actor and filmmaker Jason Bateman.
  • 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: Victoria Will
Triple: [George F. Will, hasChild, Victoria Will]
Generated description
Victoria Will is an American photographer known for her distinctive celebrity portraiture and editorial work in major publications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Victoria Will
Target entity description: Victoria Will is an American photographer known for her distinctive celebrity portraiture and editorial work in major publications.
  • A. Victoria Will chosen
    Victoria Will is an American photographer known for her distinctive celebrity portraiture and editorial work in major publications.
  • B. Victoria Grace
    Victoria Grace is an actress and voice actress known for her role in the animated series "Pacific Rim: The Black."
  • C. Victoria Prince
    Victoria Prince is an American former professional volleyball player and the wife of Kevin Federline, with whom she has twin sons.
  • D. Victoria Royal
    Victoria Royal is a central fictional member of the British monarchy in the narrative surrounding The Royal Family.
  • E. Victoria Elizabeth Bateman
    Victoria Elizabeth Bateman is the mother of American actor and filmmaker Jason Bateman.
  • F. None of above.

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_69e11e403d6481909a94d0aaf157f6ef completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf0a03c8190ac4717cce902b2cd completed April 28, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0aae734ccc8190a16b3f3350fa5ebc completed May 18, 2026, 6:15 a.m.
NEDg Description generation batch_6a0ab00780f8819086ef4d3e5756133d completed May 18, 2026, 6:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0ab0befa5481909d00cb845dd67b12 completed May 18, 2026, 6:25 a.m.
Created at: April 16, 2026, 8:37 p.m.