Triple

T21890672
Position Surface form Disambiguated ID Type / Status
Subject David Huddleston E540532 entity
Predicate spouse P13 FINISHED
Object Sarah C. Koeppe
Sarah C. Koeppe is best known as the wife of American character actor David Huddleston, who appeared in numerous film and television roles including "The Big Lebowski."
 E1540584 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: Sarah C. Koeppe | Statement: [David Huddleston, spouse, Sarah C. Koeppe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sarah C. Koeppe
Context triple: [David Huddleston, spouse, Sarah C. Koeppe]
  • A. Mary E. Vogt
    Mary E. Vogt is a film costume designer best known for her work on the 1983 dance drama "Flashdance."
  • B. Mary M. Schroeder
    Mary M. Schroeder is an American jurist who served as a judge, and later chief judge, on the U.S. Court of Appeals for the Ninth Circuit.
  • C. Sara B. Cooper
    Sara B. Cooper is a screenwriter best known for her work on the film "Lara Croft: Tomb Raider."
  • D. Mary R. Haas
    Mary R. Haas was an influential American linguist renowned for her work on Native American languages and for training a generation of field linguists.
  • E. Paula A. Kerger
    Paula A. Kerger is the longtime president and CEO of PBS, known for overseeing and expanding the public television network’s educational and cultural programming.
  • 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: Sarah C. Koeppe
Triple: [David Huddleston, spouse, Sarah C. Koeppe]
Generated description
Sarah C. Koeppe is best known as the wife of American character actor David Huddleston, who appeared in numerous film and television roles including "The Big Lebowski."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sarah C. Koeppe
Target entity description: Sarah C. Koeppe is best known as the wife of American character actor David Huddleston, who appeared in numerous film and television roles including "The Big Lebowski."
  • A. Mary E. Vogt
    Mary E. Vogt is a film costume designer best known for her work on the 1983 dance drama "Flashdance."
  • B. Mary M. Schroeder
    Mary M. Schroeder is an American jurist who served as a judge, and later chief judge, on the U.S. Court of Appeals for the Ninth Circuit.
  • C. Sara B. Cooper
    Sara B. Cooper is a screenwriter best known for her work on the film "Lara Croft: Tomb Raider."
  • D. Mary R. Haas
    Mary R. Haas was an influential American linguist renowned for her work on Native American languages and for training a generation of field linguists.
  • E. Paula A. Kerger
    Paula A. Kerger is the longtime president and CEO of PBS, known for overseeing and expanding the public television network’s educational and cultural programming.
  • 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_69e0c47a95908190ae3e19b716accb3d completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f11fc2124c8190a79cf115a1d30283 completed April 28, 2026, 8:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0b17c99b848190b9df432945b8a064 completed May 18, 2026, 1:44 p.m.
NEDg Description generation batch_6a0b18ad4f608190a6947aeb790d8be7 completed May 18, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_6a0b1979fe088190a06edb086d6b2b46 completed May 18, 2026, 1:51 p.m.
Created at: April 16, 2026, 7:06 p.m.