Triple

T10811986
Position Surface form Disambiguated ID Type / Status
Subject Two Tickets to London E255124 entity
Predicate castMember P1668 FINISHED
Object Alan Curtis
Alan Curtis was an American film and television actor active in the mid-20th century, known for his roles in crime dramas and war films.
E887441 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: Alan Curtis | Statement: [Two Tickets to London, castMember, Alan Curtis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alan Curtis
Context triple: [Two Tickets to London, castMember, Alan Curtis]
  • A. Nellee Hooper
    Nellee Hooper is a British record producer and remixer known for his influential work with artists such as U2, Björk, Massive Attack, and Madonna.
  • B. Terry Gilkyson
    Terry Gilkyson was an American folk singer and songwriter best known for penning classic Disney songs, including "The Bare Necessities" from The Jungle Book.
  • C. Allan Felder
    Allan Felder was an American songwriter and producer best known for his work in 1970s soul and R&B, particularly with the Philadelphia soul sound.
  • D. James Coryell
    James Coryell was a Texas frontiersman and early settler whose legacy is commemorated by having Coryell County, Texas, named in his honor.
  • E. Gene Lyons
    Gene Lyons was an American character actor best known for his television work in the 1950s and 1960s.
  • 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: Alan Curtis
Triple: [Two Tickets to London, castMember, Alan Curtis]
Generated description
Alan Curtis was an American film and television actor active in the mid-20th century, known for his roles in crime dramas and war films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Alan Curtis
Target entity description: Alan Curtis was an American film and television actor active in the mid-20th century, known for his roles in crime dramas and war films.
  • A. Nellee Hooper
    Nellee Hooper is a British record producer and remixer known for his influential work with artists such as U2, Björk, Massive Attack, and Madonna.
  • B. Terry Gilkyson
    Terry Gilkyson was an American folk singer and songwriter best known for penning classic Disney songs, including "The Bare Necessities" from The Jungle Book.
  • C. Allan Felder
    Allan Felder was an American songwriter and producer best known for his work in 1970s soul and R&B, particularly with the Philadelphia soul sound.
  • D. James Coryell
    James Coryell was a Texas frontiersman and early settler whose legacy is commemorated by having Coryell County, Texas, named in his honor.
  • E. Gene Lyons
    Gene Lyons was an American character actor best known for his television work in the 1950s and 1960s.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733eadda48190b2b1183ee60102cb completed April 9, 2026, 5:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69de853692f08190914cbeaf1a558730 completed April 14, 2026, 6:19 p.m.
NEDg Description generation batch_69de8954500c81909b57c4f8007959aa completed April 14, 2026, 6:37 p.m.
NED2 Entity disambiguation (via description) batch_69de8f38e3048190b1acc81bb56fe165 completed April 14, 2026, 7:02 p.m.
Created at: April 8, 2026, 9:18 p.m.