Triple

T1110012
Position Surface form Disambiguated ID Type / Status
Subject Tunbridge Wells borough E25572 entity
Predicate contains P35 FINISHED
Object Benenden
Benenden is a rural village in Kent, England, known for its historic parish church, traditional village green, and the independent girls’ school Benenden School.
 E126966 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: Benenden | Statement: [Tunbridge Wells borough, contains, Benenden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Benenden
Context triple: [Tunbridge Wells borough, contains, Benenden]
  • A. Banwen
    Banwen is a small village in South Wales, known historically for its coal mining heritage and location near the upper Dulais Valley.
  • B. Edenborn
    Edenborn is a science fiction novel by Nick Sagan that continues his post-apocalyptic series exploring genetic engineering and the future of humanity.
  • C. Breyten
    Breyten is the given name of Breyten Breytenbach, the renowned South African poet, painter, and anti-apartheid activist.
  • D. Bordon
    Bordon is a town in East Hampshire, England, historically known for its large army camp and military training facilities.
  • E. Bernardin
    Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
  • 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: Benenden
Triple: [Tunbridge Wells borough, contains, Benenden]
Generated description
Benenden is a rural village in Kent, England, known for its historic parish church, traditional village green, and the independent girls’ school Benenden School.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Benenden
Target entity description: Benenden is a rural village in Kent, England, known for its historic parish church, traditional village green, and the independent girls’ school Benenden School.
  • A. Banwen
    Banwen is a small village in South Wales, known historically for its coal mining heritage and location near the upper Dulais Valley.
  • B. Edenborn
    Edenborn is a science fiction novel by Nick Sagan that continues his post-apocalyptic series exploring genetic engineering and the future of humanity.
  • C. Breyten
    Breyten is the given name of Breyten Breytenbach, the renowned South African poet, painter, and anti-apartheid activist.
  • D. Bordon
    Bordon is a town in East Hampshire, England, historically known for its large army camp and military training facilities.
  • E. Bernardin
    Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
  • 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_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4ba045fd88190982e1c6278fb9ca3 completed March 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c4f65888190b48c2d220e62a26b completed March 7, 2026, 4:03 p.m.
NEDg Description generation batch_69ac500036f48190bab0bf4e07d5c9ae completed March 7, 2026, 4:19 p.m.
NED2 Entity disambiguation (via description) batch_69ac508ca8e48190bfea6ad9b6920e78 completed March 7, 2026, 4:21 p.m.
Created at: March 1, 2026, 7:43 p.m.