Triple

T10819397
Position Surface form Disambiguated ID Type / Status
Subject Don Beyer E255323 entity
Predicate spouse P13 FINISHED
Object Megan Beyer
Megan Beyer is an American journalist and civic leader known for her work in cultural diplomacy, gender equality, and public policy initiatives.
E887778 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: Megan Beyer | Statement: [Don Beyer, spouse, Megan Beyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Megan Beyer
Context triple: [Don Beyer, spouse, Megan Beyer]
  • A. Megan Gustafson
    Megan Gustafson is an American professional basketball player and former Iowa Hawkeyes star known for her dominant post play and national player of the year honors in college.
  • B. Megan Ferguson
    Megan Ferguson is an American actress known for her work in television comedies and dramas, including a prominent role in the series "The Comedians."
  • C. Megan Foster
    Megan Foster is an American local government leader serving as the mayor of Coralville, Iowa.
  • D. Bethany Balcer
    Bethany Balcer is an American professional soccer forward known for her prolific goal scoring in the National Women's Soccer League.
  • E. Kirsten Beyer
    Kirsten Beyer is an American author and television writer best known for her work on Star Trek novels and for helping develop and write modern Star Trek series such as Star Trek: Discovery and Star Trek: Picard.
  • 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: Megan Beyer
Triple: [Don Beyer, spouse, Megan Beyer]
Generated description
Megan Beyer is an American journalist and civic leader known for her work in cultural diplomacy, gender equality, and public policy initiatives.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Megan Beyer
Target entity description: Megan Beyer is an American journalist and civic leader known for her work in cultural diplomacy, gender equality, and public policy initiatives.
  • A. Megan Gustafson
    Megan Gustafson is an American professional basketball player and former Iowa Hawkeyes star known for her dominant post play and national player of the year honors in college.
  • B. Megan Ferguson
    Megan Ferguson is an American actress known for her work in television comedies and dramas, including a prominent role in the series "The Comedians."
  • C. Megan Foster
    Megan Foster is an American local government leader serving as the mayor of Coralville, Iowa.
  • D. Bethany Balcer
    Bethany Balcer is an American professional soccer forward known for her prolific goal scoring in the National Women's Soccer League.
  • E. Kirsten Beyer
    Kirsten Beyer is an American author and television writer best known for her work on Star Trek novels and for helping develop and write modern Star Trek series such as Star Trek: Discovery and Star Trek: Picard.
  • 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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d734492be88190874ea0ba4d0fa643 completed April 9, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69de8569178481909474e939a3e4c217 completed April 14, 2026, 6:20 p.m.
NEDg Description generation batch_69de8955b9d8819086ff98efbff6c7a0 completed April 14, 2026, 6:37 p.m.
NED2 Entity disambiguation (via description) batch_69de8f4a318c819086559fd53506ab29 completed April 14, 2026, 7:02 p.m.
Created at: April 8, 2026, 9:18 p.m.