Triple

T13754397
Position Surface form Disambiguated ID Type / Status
Subject Haughley E330436 entity
Predicate civilParishIncludes P852 FINISHED
Object Haughley Green
Haughley Green is a small settlement in Suffolk, England, forming part of the rural community around the village of Haughley.
E1061688 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: Haughley Green | Statement: [Haughley, civilParishIncludes, Haughley Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haughley Green
Context triple: [Haughley, civilParishIncludes, Haughley Green]
  • A. Hatfield Heath
    Hatfield Heath is a village and civil parish in the Uttlesford district of Essex, England, known for its large village green and rural character.
  • B. Hoggen Green
    Hoggen Green is the former name of College Green, a historic public space in central Dublin, Ireland.
  • C. Wylde Green
    Wylde Green is a suburban railway station in the West Midlands, England, serving the Wylde Green area of Sutton Coldfield on the Cross-City Line.
  • D. Letchmore Heath
    Letchmore Heath is a small, picturesque village in Hertfordshire, England, known for its traditional village green and historic rural character.
  • E. Langton Green
    Langton Green is a village in Kent, England, situated near Tunbridge Wells and known for its residential character and local community amenities.
  • 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: Haughley Green
Triple: [Haughley, civilParishIncludes, Haughley Green]
Generated description
Haughley Green is a small settlement in Suffolk, England, forming part of the rural community around the village of Haughley.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haughley Green
Target entity description: Haughley Green is a small settlement in Suffolk, England, forming part of the rural community around the village of Haughley.
  • A. Hatfield Heath
    Hatfield Heath is a village and civil parish in the Uttlesford district of Essex, England, known for its large village green and rural character.
  • B. Hoggen Green
    Hoggen Green is the former name of College Green, a historic public space in central Dublin, Ireland.
  • C. Wylde Green
    Wylde Green is a suburban railway station in the West Midlands, England, serving the Wylde Green area of Sutton Coldfield on the Cross-City Line.
  • D. Letchmore Heath
    Letchmore Heath is a small, picturesque village in Hertfordshire, England, known for its traditional village green and historic rural character.
  • E. Langton Green
    Langton Green is a village in Kent, England, situated near Tunbridge Wells and known for its residential character and local community amenities.
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02179c948190a652cc8c586e418f completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b06d9fd48190a10b86a0d68fac70 completed May 3, 2026, 8:30 p.m.
NEDg Description generation batch_69f7b11b824881909ed068c7d608d956 completed May 3, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_69f7b1e0ab948190a046a68aa5e029a6 completed May 3, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:09 p.m.