Triple

T8449588
Position Surface form Disambiguated ID Type / Status
Subject The War Zone E199767 entity
Predicate stars P1956 FINISHED
Object Freddie Cunliffe
Freddie Cunliffe is a British actor best known for his role in the 1999 war drama film "The War Zone."
 E735047 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: Freddie Cunliffe | Statement: [The War Zone, stars, Freddie Cunliffe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Freddie Cunliffe
Context triple: [The War Zone, stars, Freddie Cunliffe]
  • A. Freddie Bullivant
    Freddie Bullivant is the central character of the show "Fixing it for Freddie," around whom the series’ stories and events revolve.
  • B. Charles McNaughton
    Charles McNaughton was a British actor active in the early 20th century, known for his character roles in films and on stage.
  • C. Edward Shearmur
    Edward Shearmur is a British film composer known for his orchestral scores for a wide range of Hollywood movies and television projects.
  • D. Nicholas Crane
    Nicholas Crane is a British geographer, author, and television presenter known for his work on geography-themed documentaries and popular science books.
  • E. Freddie Young
    Freddie Young was a renowned British cinematographer best known for his sweeping, visually stunning work on epic films such as "Lawrence of Arabia."
  • 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: Freddie Cunliffe
Triple: [The War Zone, stars, Freddie Cunliffe]
Generated description
Freddie Cunliffe is a British actor best known for his role in the 1999 war drama film "The War Zone."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Freddie Cunliffe
Target entity description: Freddie Cunliffe is a British actor best known for his role in the 1999 war drama film "The War Zone."
  • A. Freddie Bullivant
    Freddie Bullivant is the central character of the show "Fixing it for Freddie," around whom the series’ stories and events revolve.
  • B. Charles McNaughton
    Charles McNaughton was a British actor active in the early 20th century, known for his character roles in films and on stage.
  • C. Edward Shearmur
    Edward Shearmur is a British film composer known for his orchestral scores for a wide range of Hollywood movies and television projects.
  • D. Nicholas Crane
    Nicholas Crane is a British geographer, author, and television presenter known for his work on geography-themed documentaries and popular science books.
  • E. Freddie Young
    Freddie Young was a renowned British cinematographer best known for his sweeping, visually stunning work on epic films such as "Lawrence of Arabia."
  • 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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe44707b88190b3d8b30c45ef4496 completed March 31, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1dc85e48819083340d022d0dba9b completed April 2, 2026, 7:42 a.m.
NEDg Description generation batch_69ce1f88d404819096c6024c0e61d1ea completed April 2, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69ce209338b48190ba8375200a5529bd completed April 2, 2026, 7:53 a.m.
Created at: March 30, 2026, 6:09 p.m.