Triple

T4532389
Position Surface form Disambiguated ID Type / Status
Subject Things to Come E106326 entity
Predicate setInLocation P40 FINISHED
Object Everytown
Everytown is a fictional futuristic British city depicted in the 1936 science fiction film "Things to Come," representing an idealized, technologically advanced society.
 E450632 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: Everytown | Statement: [Things to Come, setInLocation, Everytown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Everytown
Context triple: [Things to Come, setInLocation, Everytown]
  • A. Red Town
    Red Town is a historical region associated with the settlement of Krasnaya Sloboda, known for its cultural and regional significance.
  • B. B-Town
    B-Town is a common nickname for Bloomington, Indiana, a vibrant Midwestern college city best known as the home of Indiana University.
  • C. O-Town
    O-Town is an American boy band formed on the reality TV series "Making the Band," known for early-2000s pop hits like "Liquid Dreams" and "All or Nothing."
  • D. O-Town
    O-Town is a popular nickname for the city of Orlando, Florida, often used in local culture and media.
  • E. City on a Hill
    City on a Hill is a film produced by Little Mountain Films, likely centered on socially conscious or character-driven storytelling.
  • 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: Everytown
Triple: [Things to Come, setInLocation, Everytown]
Generated description
Everytown is a fictional futuristic British city depicted in the 1936 science fiction film "Things to Come," representing an idealized, technologically advanced society.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Everytown
Target entity description: Everytown is a fictional futuristic British city depicted in the 1936 science fiction film "Things to Come," representing an idealized, technologically advanced society.
  • A. Red Town
    Red Town is a historical region associated with the settlement of Krasnaya Sloboda, known for its cultural and regional significance.
  • B. B-Town
    B-Town is a common nickname for Bloomington, Indiana, a vibrant Midwestern college city best known as the home of Indiana University.
  • C. O-Town
    O-Town is an American boy band formed on the reality TV series "Making the Band," known for early-2000s pop hits like "Liquid Dreams" and "All or Nothing."
  • D. O-Town
    O-Town is a popular nickname for the city of Orlando, Florida, often used in local culture and media.
  • E. City on a Hill
    City on a Hill is a film produced by Little Mountain Films, likely centered on socially conscious or character-driven storytelling.
  • 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd579f27ac8190ae9a4252109e56e1 completed March 20, 2026, 2:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdace3a81c8190963ea65fa3df23c0 completed March 20, 2026, 8:24 p.m.
NEDg Description generation batch_69bdad6a522c8190a490347d3fe623e8 completed March 20, 2026, 8:26 p.m.
NED2 Entity disambiguation (via description) batch_69bdadd612a48190b088fe6ac894dbb5 completed March 20, 2026, 8:28 p.m.
Created at: March 20, 2026, 1:03 p.m.