Triple

T13831013
Position Surface form Disambiguated ID Type / Status
Subject Van Wilder E332397 entity
Predicate writer P1360 FINISHED
Object Brent Goldberg
Brent Goldberg is a screenwriter best known for co-writing the college comedy film "Van Wilder."
 E1064759 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: Brent Goldberg | Statement: [Van Wilder, writer, Brent Goldberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Brent Goldberg
Context triple: [Van Wilder, writer, Brent Goldberg]
  • A. John Briscoe
    John Briscoe was a renowned engineer and water resources expert recognized globally for his contributions to water management and policy.
  • B. Mark Henry
    Mark Henry is a retired American professional wrestler and former Olympic weightlifter best known for his powerful "World's Strongest Man" persona in WWE.
  • C. Mike Kershaw
    Mike Kershaw is a software developer best known for creating the wireless network detector and sniffer tool Kismet.
  • D. Jimmy Ross
    Jimmy Ross was a prominent Scottish inside forward of the late 19th century, best known for his prolific goal-scoring and key role in Preston North End’s legendary “Invincibles” team.
  • E. Luther Van Dam
    Luther Van Dam is a bumbling yet lovable assistant football coach on the sitcom "Coach," known for his comedic antics and loyalty to head coach Hayden Fox.
  • 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: Brent Goldberg
Triple: [Van Wilder, writer, Brent Goldberg]
Generated description
Brent Goldberg is a screenwriter best known for co-writing the college comedy film "Van Wilder."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Brent Goldberg
Target entity description: Brent Goldberg is a screenwriter best known for co-writing the college comedy film "Van Wilder."
  • A. John Briscoe
    John Briscoe was a renowned engineer and water resources expert recognized globally for his contributions to water management and policy.
  • B. Mark Henry
    Mark Henry is a retired American professional wrestler and former Olympic weightlifter best known for his powerful "World's Strongest Man" persona in WWE.
  • C. Mike Kershaw
    Mike Kershaw is a software developer best known for creating the wireless network detector and sniffer tool Kismet.
  • D. Jimmy Ross
    Jimmy Ross was a prominent Scottish inside forward of the late 19th century, best known for his prolific goal-scoring and key role in Preston North End’s legendary “Invincibles” team.
  • E. Luther Van Dam
    Luther Van Dam is a bumbling yet lovable assistant football coach on the sitcom "Coach," known for his comedic antics and loyalty to head coach Hayden Fox.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0299334481908c2b271eaf06e4b7 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8ebf2608190b1071ee6967fa8d3 completed May 3, 2026, 9:06 p.m.
NEDg Description generation batch_69f7b9d928ac81908867a99740d6c3a0 completed May 3, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_69f7ba6b2c208190b01e3a5ae872b14f completed May 3, 2026, 9:13 p.m.
Created at: April 9, 2026, 10:13 p.m.