Triple

T2624803
Position Surface form Disambiguated ID Type / Status
Subject Madame Secretary E59091 entity
Predicate character P662 FINISHED
Object Blake Moran
Blake Moran is a key fictional aide and policy advisor to the U.S. Secretary of State in the political drama television series "Madam Secretary."
E282953 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: Blake Moran | Statement: [Madame Secretary, character, Blake Moran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blake Moran
Context triple: [Madame Secretary, character, Blake Moran]
  • A. David Blunt
    David Blunt is a British football executive best known for serving as chairman of Doncaster Rovers Football Club.
  • B. Steve McMorran
    Steve McMorran is a music producer and songwriter known for his work on James Blunt’s hit album "Back to Bedlam" and collaborations across pop and country genres.
  • C. Sean Mortimer
    Sean Mortimer is a music video director known for his work with the artist Juicy.
  • D. Andrew Duggan
    Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
  • E. Iain Farrington
    Iain Farrington is a British pianist, organist, composer, and arranger known for his versatile work across classical and contemporary music, including high-profile national events.
  • 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: Blake Moran
Triple: [Madame Secretary, character, Blake Moran]
Generated description
Blake Moran is a key fictional aide and policy advisor to the U.S. Secretary of State in the political drama television series "Madam Secretary."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Blake Moran
Target entity description: Blake Moran is a key fictional aide and policy advisor to the U.S. Secretary of State in the political drama television series "Madam Secretary."
  • A. David Blunt
    David Blunt is a British football executive best known for serving as chairman of Doncaster Rovers Football Club.
  • B. Steve McMorran
    Steve McMorran is a music producer and songwriter known for his work on James Blunt’s hit album "Back to Bedlam" and collaborations across pop and country genres.
  • C. Sean Mortimer
    Sean Mortimer is a music video director known for his work with the artist Juicy.
  • D. Andrew Duggan
    Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
  • E. Iain Farrington
    Iain Farrington is a British pianist, organist, composer, and arranger known for his versatile work across classical and contemporary music, including high-profile national events.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8b061a08190b7a8459851abaae2 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af909b7d9881908930a98d004998fb completed March 10, 2026, 3:31 a.m.
NEDg Description generation batch_69af913e20848190a25c90617df6ea6f completed March 10, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_69af91e0ef408190b1ab9cb9f8bbdaca completed March 10, 2026, 3:37 a.m.
Created at: March 6, 2026, 9:50 p.m.