Triple

T1180757
Position Surface form Disambiguated ID Type / Status
Subject Flightplan E25130 entity
Predicate starring P1507 FINISHED
Object Kate Beahan
Kate Beahan is an Australian actress known for her roles in films such as "Flightplan" and "The Wicker Man."
E217858 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: Kate Beahan | Statement: [Flightplan, starring, Kate Beahan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Beahan
Context triple: [Flightplan, starring, Kate Beahan]
  • A. Nicole Shanahan
    Nicole Shanahan is an American attorney, legal tech entrepreneur, and philanthropist known for founding the patent management company ClearAccessIP and for her high-profile marriage to Google co-founder Sergey Brin.
  • B. Erin McDermott
    Erin McDermott is a collegiate sports administrator best known as the athletic director at Harvard University.
  • C. Janel Moloney
    Janel Moloney is an American actress best known for her role as Donna Moss on the political drama television series "The West Wing."
  • D. Kirsten Corley
    Kirsten Corley is an American former model and real estate agent best known as the wife of hip-hop artist Chance the Rapper.
  • E. Alana Beard
    Alana Beard is a former American professional basketball player and four-time WNBA All-Star known for her elite perimeter defense and key role in the league during the 2000s and 2010s.
  • 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: Kate Beahan
Triple: [Flightplan, starring, Kate Beahan]
Generated description
Kate Beahan is an Australian actress known for her roles in films such as "Flightplan" and "The Wicker Man."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kate Beahan
Target entity description: Kate Beahan is an Australian actress known for her roles in films such as "Flightplan" and "The Wicker Man."
  • A. Nicole Shanahan
    Nicole Shanahan is an American attorney, legal tech entrepreneur, and philanthropist known for founding the patent management company ClearAccessIP and for her high-profile marriage to Google co-founder Sergey Brin.
  • B. Erin McDermott
    Erin McDermott is a collegiate sports administrator best known as the athletic director at Harvard University.
  • C. Janel Moloney
    Janel Moloney is an American actress best known for her role as Donna Moss on the political drama television series "The West Wing."
  • D. Kirsten Corley
    Kirsten Corley is an American former model and real estate agent best known as the wife of hip-hop artist Chance the Rapper.
  • E. Alana Beard
    Alana Beard is a former American professional basketball player and four-time WNBA All-Star known for her elite perimeter defense and key role in the league during the 2000s and 2010s.
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd32c5f48190b4e2d39fa052cbb7 completed March 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb8231ec81909d539f9bc2219619 completed March 8, 2026, 10:43 p.m.
NEDg Description generation batch_69adfbf98f508190a237a2067bf0574f completed March 8, 2026, 10:45 p.m.
NED2 Entity disambiguation (via description) batch_69adfc523d248190a1d748c7a9579d06 completed March 8, 2026, 10:46 p.m.
Created at: March 1, 2026, 7:45 p.m.