Triple

T12531170
Position Surface form Disambiguated ID Type / Status
Subject Suffragette E299565 entity
Predicate filmingLocation P40 FINISHED
Object Kent
Kent is a county in southeastern England known for its historic towns, coastal landscapes, and frequent use as a filming location for British film and television productions.
E5977 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: Kent | Statement: [Suffragette, filmingLocation, Kent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kent
Context triple: [Suffragette, filmingLocation, Kent]
  • A. Kent
    Kent is a suburban city in King County, Washington, known as a residential and industrial hub within the greater Seattle metropolitan area.
  • B. Kent
    Kent is a villainous saloon owner and primary antagonist in the classic 1939 Western film "Destry Rides Again."
  • C. Kent
    Kent is a small district municipality in British Columbia, Canada, known for its agricultural lands and proximity to the Fraser River.
  • D. Kent
    Kent is a brand of filtered cigarettes historically marketed as a "safer" smoking option and produced by the Lorillard Tobacco Company.
  • E. Kent
    Kent is a common English surname famously associated with the adoptive family of Superman in DC Comics, including Jonathan and Martha Kent.
  • 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: Kent
Triple: [Suffragette, filmingLocation, Kent]
Generated description
Kent is a county in southeastern England known for its historic towns, coastal landscapes, and frequent use as a filming location for British film and television productions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kent
Target entity description: Kent is a county in southeastern England known for its historic towns, coastal landscapes, and frequent use as a filming location for British film and television productions.
  • A. Kent chosen
    Kent is a county in southeastern England known for its historic towns, coastal landscapes, and nickname "the Garden of England."
  • B. Kent
    Kent is a small district municipality in British Columbia, Canada, known for its agricultural lands and proximity to the Fraser River.
  • C. Kent
    Kent is a suburban city in King County, Washington, known as a residential and industrial hub within the greater Seattle metropolitan area.
  • D. Kent
    Kent is a common English surname borne by numerous notable individuals across fields such as art, politics, and entertainment.
  • E. Kent
    Kent is a common English surname famously associated with the adoptive family of Superman in DC Comics, including Jonathan and Martha Kent.
  • F. None of above.

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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d95469d100819087c83bc55e3ec9ce completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bab99bc8190abe6dfb7c6a7fe6f completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64c276d388190b58fe884466076ee completed May 2, 2026, 7:10 p.m.
NED2 Entity disambiguation (via description) batch_69f64ce7b444819094d94bec749d7618 completed May 2, 2026, 7:13 p.m.
Created at: April 8, 2026, 9:57 p.m.