Triple

T10390726
Position Surface form Disambiguated ID Type / Status
Subject The Gray Man E244884 entity
Predicate antagonistCharacter P18963 FINISHED
Object Lloyd Hansen
Lloyd Hansen is the ruthless and unhinged former CIA operative who serves as the primary villain in the action thriller film "The Gray Man."
E901775 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: Lloyd Hansen | Statement: [The Gray Man, antagonistCharacter, Lloyd Hansen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lloyd Hansen
Context triple: [The Gray Man, antagonistCharacter, Lloyd Hansen]
  • A. George Hansen
    George Hansen is a fictional character from the 1958 Western film "Terror in a Texas Town."
  • B. Larry Bryggman
    Larry Bryggman is an American actor best known for his long-running role on the soap opera "As the World Turns" and various film and television appearances.
  • C. Ole Hanson
    Ole Hanson was an American real estate developer and former mayor of Seattle best known for envisioning and developing the master-planned coastal community of San Clemente, California.
  • D. Ron Jensen
    Ron Jensen is an American politician who has served as the mayor of Grand Prairie, Texas.
  • E. Paul Henning
    Paul Henning was an American television and film writer-producer best known for creating the classic sitcom "The Beverly Hillbillies" and shaping 1960s rural comedy on TV.
  • 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: Lloyd Hansen
Triple: [The Gray Man, antagonistCharacter, Lloyd Hansen]
Generated description
Lloyd Hansen is the ruthless and unhinged former CIA operative who serves as the primary villain in the action thriller film "The Gray Man."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lloyd Hansen
Target entity description: Lloyd Hansen is the ruthless and unhinged former CIA operative who serves as the primary villain in the action thriller film "The Gray Man."
  • A. George Hansen
    George Hansen is a fictional character from the 1958 Western film "Terror in a Texas Town."
  • B. Larry Bryggman
    Larry Bryggman is an American actor best known for his long-running role on the soap opera "As the World Turns" and various film and television appearances.
  • C. Ole Hanson
    Ole Hanson was an American real estate developer and former mayor of Seattle best known for envisioning and developing the master-planned coastal community of San Clemente, California.
  • D. Ron Jensen
    Ron Jensen is an American politician who has served as the mayor of Grand Prairie, Texas.
  • E. Paul Henning
    Paul Henning was an American television and film writer-producer best known for creating the classic sitcom "The Beverly Hillbillies" and shaping 1960s rural comedy on TV.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b4f7d08190bcb16d3b4c8f22ad completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3a8c95ca081908ceaa89eef87fbc9 completed April 18, 2026, 3:52 p.m.
NEDg Description generation batch_69e3abe492388190a2f5752f6bad1220 completed April 18, 2026, 4:05 p.m.
NED2 Entity disambiguation (via description) batch_69e3b1efe4a88190884eb5186954cf39 completed April 18, 2026, 4:31 p.m.
Created at: April 6, 2026, 12:06 p.m.