Triple

T22225323
Position Surface form Disambiguated ID Type / Status
Subject Into the Storm E549323 entity
Predicate producer P490 FINISHED
Object Frank Doelger
Frank Doelger is an Emmy-winning television producer best known for his work on acclaimed HBO dramas such as "Game of Thrones" and "John Adams."
 E443540 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: Frank Doelger | Statement: [Into the Storm, producer, Frank Doelger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Frank Doelger
Context triple: [Into the Storm, producer, Frank Doelger]
  • A. Frank Doelger
    Frank Doelger is a television producer best known for his work on the acclaimed HBO fantasy series "Game of Thrones."
  • B. John Diehl
    John Diehl is an American character actor best known for his role as Detective Larry Zito on the 1980s television series "Miami Vice."
  • C. Craig Doerge
    Craig Doerge is an American keyboardist, songwriter, and session musician best known for his work with Jackson Browne, Crosby, Stills & Nash, and other prominent rock and folk-rock artists of the 1970s and 1980s.
  • D. Andrew Doerfer
    Andrew Doerfer is a film editor best known for his work on the movie "Iron Will."
  • E. John Eisendrath
    John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
  • 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: Frank Doelger
Triple: [Into the Storm, producer, Frank Doelger]
Generated description
Frank Doelger is an Emmy-winning television producer best known for his work on acclaimed HBO dramas such as "Game of Thrones" and "John Adams."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Frank Doelger
Target entity description: Frank Doelger is an Emmy-winning television producer best known for his work on acclaimed HBO dramas such as "Game of Thrones" and "John Adams."
  • A. Frank Doelger chosen
    Frank Doelger is a television producer best known for his work on the acclaimed HBO fantasy series "Game of Thrones."
  • B. John Diehl
    John Diehl is an American character actor best known for his role as Detective Larry Zito on the 1980s television series "Miami Vice."
  • C. Craig Doerge
    Craig Doerge is an American keyboardist, songwriter, and session musician best known for his work with Jackson Browne, Crosby, Stills & Nash, and other prominent rock and folk-rock artists of the 1970s and 1980s.
  • D. Andrew Doerfer
    Andrew Doerfer is a film editor best known for his work on the movie "Iron Will."
  • E. John Eisendrath
    John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
  • 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_69f12b93e2208190aee70ffd82962ea0 completed April 28, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0ba791d9ec81908a518673ed3dd04b completed May 18, 2026, 11:58 p.m.
NEDg Description generation batch_6a0ba81bade88190bc0f4225600509a2 completed May 19, 2026, midnight
NED2 Entity disambiguation (via description) batch_6a0ba8c3d6c88190944df9358dd58c4e completed May 19, 2026, 12:03 a.m.
Created at: April 16, 2026, 8:37 p.m.