Triple

T12657367
Position Surface form Disambiguated ID Type / Status
Subject 8 Seconds E302319 entity
Predicate basedOn P98 FINISHED
Object life of Lane Frost
The life of Lane Frost centers on the brief, celebrated career and tragic death of the charismatic American professional bull rider who became a rodeo legend.
 E995350 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: life of Lane Frost | Statement: [8 Seconds, basedOn, life of Lane Frost]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: life of Lane Frost
Context triple: [8 Seconds, basedOn, life of Lane Frost]
  • A. Jesus Lane
    Jesus Lane is a historic street in central Cambridge, England, known for its proximity to several colleges and notable university buildings.
  • B. The Lanes
    The Lanes is a famous historic quarter in Brighton known for its narrow winding streets lined with independent shops, cafes, and boutiques.
  • C. The Lanes
    The Lanes is a historic, narrow-street shopping and leisure quarter in central Norwich, known for its independent boutiques, cafes, and medieval character.
  • D. Layne
    Layne is a given name used for both males and females, often considered a variant spelling of the name Lane.
  • E. Lola Lane
    Lola Lane was an American film actress best known as one of the Lane Sisters, who appeared in numerous Hollywood productions during the 1930s and 1940s.
  • 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: life of Lane Frost
Triple: [8 Seconds, basedOn, life of Lane Frost]
Generated description
The life of Lane Frost centers on the brief, celebrated career and tragic death of the charismatic American professional bull rider who became a rodeo legend.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: life of Lane Frost
Target entity description: The life of Lane Frost centers on the brief, celebrated career and tragic death of the charismatic American professional bull rider who became a rodeo legend.
  • A. Jesus Lane
    Jesus Lane is a historic street in central Cambridge, England, known for its proximity to several colleges and notable university buildings.
  • B. The Lanes
    The Lanes is a famous historic quarter in Brighton known for its narrow winding streets lined with independent shops, cafes, and boutiques.
  • C. The Lanes
    The Lanes is a historic, narrow-street shopping and leisure quarter in central Norwich, known for its independent boutiques, cafes, and medieval character.
  • D. Layne
    Layne is a given name used for both males and females, often considered a variant spelling of the name Lane.
  • E. Lola Lane
    Lola Lane was an American film actress best known as one of the Lane Sisters, who appeared in numerous Hollywood productions during the 1930s and 1940s.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961636db8819099c438b24bcfd866 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f668832c7081909eb75429efba493e completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f6697e3a688190abd025df1112feba completed May 2, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_69f66a9230608190bfe99290ca1679fa completed May 2, 2026, 9:20 p.m.
Created at: April 9, 2026, 5:18 p.m.