Triple

T14365776
Position Surface form Disambiguated ID Type / Status
Subject Dean Paul Larson E356229 entity
Predicate name P16 FINISHED
Object Dean Paul Larson
Dean Paul Larson is an individual whose specific public background or notable achievements are not clearly documented in widely available sources.
 E356229 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: Dean Paul Larson | Statement: [Dean Paul Larson, name, Dean Paul Larson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dean Paul Larson
Context triple: [Dean Paul Larson, name, Dean Paul Larson]
  • A. Dean Paul Larson
    Dean Paul Larson is a fictional character from the television series "The Chair."
  • B. Michael Larsen
    Michael Larsen is the person credited with coining the now-popular term “Painted Ladies” to describe the colorfully restored Victorian and Edwardian houses of San Francisco.
  • C. Dan Paulson
    Dan Paulson is a film and television producer best known for his work on action films like "Passenger 57."
  • D. Matt Larson
    Matt Larson is an Internet engineer and author known for his work on DNS standards and contributions to key IETF documents.
  • E. Darrell Larson
    Darrell Larson is an American actor and director known for his character roles in film and television since the 1970s.
  • 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: Dean Paul Larson
Triple: [Dean Paul Larson, name, Dean Paul Larson]
Generated description
Dean Paul Larson is an individual whose specific public background or notable achievements are not clearly documented in widely available sources.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dean Paul Larson
Target entity description: Dean Paul Larson is an individual whose specific public background or notable achievements are not clearly documented in widely available sources.
  • A. Dean Paul Larson chosen
    Dean Paul Larson is a fictional character from the television series "The Chair."
  • B. Michael Larsen
    Michael Larsen is the person credited with coining the now-popular term “Painted Ladies” to describe the colorfully restored Victorian and Edwardian houses of San Francisco.
  • C. Dan Paulson
    Dan Paulson is a film and television producer best known for his work on action films like "Passenger 57."
  • D. Matt Larson
    Matt Larson is an Internet engineer and author known for his work on DNS standards and contributions to key IETF documents.
  • E. Darrell Larson
    Darrell Larson is an American actor and director known for his character roles in film and television since the 1970s.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fad48748190a0f34ca4d02f9a3c completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd550e677c8190837c3b9ccb64f0cd completed May 8, 2026, 3:14 a.m.
NEDg Description generation batch_69fd5637a46881908f3a4b26cc2159ca completed May 8, 2026, 3:19 a.m.
NED2 Entity disambiguation (via description) batch_69fd56ae779c81908e09866913df3e3e completed May 8, 2026, 3:21 a.m.
Created at: April 10, 2026, 1:15 a.m.