Triple

T3089620
Position Surface form Disambiguated ID Type / Status
Subject Suffolk E64456 entity
Predicate containsSettlement P847 FINISHED
Object Fressingfield
Fressingfield is a rural village and civil parish in the county of Suffolk in eastern England, known for its historic church and traditional countryside setting.
 E330662 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: Fressingfield | Statement: [Suffolk, containsSettlement, Fressingfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fressingfield
Context triple: [Suffolk, containsSettlement, Fressingfield]
  • A. Glemsford
    Glemsford is a village and civil parish in the county of Suffolk in eastern England, known for its historic buildings and rural character.
  • B. Boxford
    Boxford is a village and civil parish in Suffolk, England, known for its historic buildings and rural character.
  • C. Sandisfield
    Sandisfield is a small rural town in southwestern Massachusetts known for its forests, reservoirs, and quiet, sparsely populated landscape.
  • D. Freckenham
    Freckenham is a small rural village and civil parish located in the English county of Suffolk.
  • E. Lavenham
    Lavenham is a historic medieval wool town in Suffolk, England, renowned for its well-preserved timber-framed buildings and picturesque streets.
  • 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: Fressingfield
Triple: [Suffolk, containsSettlement, Fressingfield]
Generated description
Fressingfield is a rural village and civil parish in the county of Suffolk in eastern England, known for its historic church and traditional countryside setting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fressingfield
Target entity description: Fressingfield is a rural village and civil parish in the county of Suffolk in eastern England, known for its historic church and traditional countryside setting.
  • A. Glemsford
    Glemsford is a village and civil parish in the county of Suffolk in eastern England, known for its historic buildings and rural character.
  • B. Boxford
    Boxford is a village and civil parish in Suffolk, England, known for its historic buildings and rural character.
  • C. Sandisfield
    Sandisfield is a small rural town in southwestern Massachusetts known for its forests, reservoirs, and quiet, sparsely populated landscape.
  • D. Freckenham
    Freckenham is a small rural village and civil parish located in the English county of Suffolk.
  • E. Lavenham
    Lavenham is a historic medieval wool town in Suffolk, England, renowned for its well-preserved timber-framed buildings and picturesque streets.
  • 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_69ad857c97d88190b26f9b1c90839c77 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada20d8f788190b05b8b6b5042bc1a completed March 8, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224bff19c8190b28c07e3fb018853 completed March 12, 2026, 2:28 a.m.
NEDg Description generation batch_69b22557dd4c8190841800d39b328d77 completed March 12, 2026, 2:30 a.m.
NED2 Entity disambiguation (via description) batch_69b225b352f48190825859a862a57fd1 completed March 12, 2026, 2:32 a.m.
Created at: March 8, 2026, 3:03 p.m.