Triple

T3621625
Position Surface form Disambiguated ID Type / Status
Subject Ron Burgundy E76739 entity
Predicate givenName P17 FINISHED
Object Ron
Ron is the first name of Ron Burgundy, the fictional, egotistical 1970s news anchor from the comedy film "Anchorman."
 E117761 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: Ron | Statement: [Ron Burgundy, givenName, Ron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ron
Context triple: [Ron Burgundy, givenName, Ron]
  • A. Ron
    Ron is a West Chadic language spoken in parts of central Nigeria.
  • B. Ron
    Ron is the commonly used first name of American politician Ron DeSantis, the governor of Florida and a prominent figure in contemporary U.S. conservative politics.
  • C. Rob
    Rob is a common shortened form of the given name Robert, frequently used as an informal or familiar first name.
  • D. Rick
    Rick is the common nickname of Rick Adelman, a former professional basketball player and longtime NBA head coach best known for leading the Portland Trail Blazers and Sacramento Kings.
  • E. Rick
    Rick is the introspective, emotionally adrift Hollywood screenwriter who serves as the central figure in Terrence Malick’s film "Knight of Cups."
  • 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: Ron
Triple: [Ron Burgundy, givenName, Ron]
Generated description
Ron is the first name of Ron Burgundy, the fictional, egotistical 1970s news anchor from the comedy film "Anchorman."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ron
Target entity description: Ron is the first name of Ron Burgundy, the fictional, egotistical 1970s news anchor from the comedy film "Anchorman."
  • A. Ron chosen
    Ron is the commonly used first name of American politician Ron DeSantis, the governor of Florida and a prominent figure in contemporary U.S. conservative politics.
  • B. Ron
    Ron is a West Chadic language spoken in parts of central Nigeria.
  • C. Rob
    Rob is a common shortened form of the given name Robert, frequently used as an informal or familiar first name.
  • D. Rick
    Rick is the common nickname of Rick Adelman, a former professional basketball player and longtime NBA head coach best known for leading the Portland Trail Blazers and Sacramento Kings.
  • E. Rick
    Rick is the introspective, emotionally adrift Hollywood screenwriter who serves as the central figure in Terrence Malick’s film "Knight of Cups."
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2bb12cc8190bd67597cf3b66a3a completed March 8, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4331e75d08190ad1ce3e7ef26454a completed March 13, 2026, 3:54 p.m.
NEDg Description generation batch_69b436140e9c81909c0616e6fce36c2b completed March 13, 2026, 4:06 p.m.
NED2 Entity disambiguation (via description) batch_69b439c83580819091024e692847a7db completed March 13, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:23 p.m.