Triple

T9746222
Position Surface form Disambiguated ID Type / Status
Subject Warlingham E236314 entity
Predicate hasLandmark P105 FINISHED
Object Warlingham Green
Warlingham Green is a central village green and focal public space in Warlingham, Surrey, surrounded by local shops, pubs, and community amenities.
E819590 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: Warlingham Green | Statement: [Warlingham, hasLandmark, Warlingham Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warlingham Green
Context triple: [Warlingham, hasLandmark, Warlingham Green]
  • A. Langley Green
    Langley Green is a residential neighbourhood within the town of Crawley in West Sussex, England.
  • B. Southwick Green
    Southwick Green is a central public green and recreational open space in the village of Southwick, West Sussex, England.
  • C. Palmers Green
    Palmers Green is a suburban area in the London Borough of Enfield, known for its residential character and significant Greek and Cypriot community.
  • D. Talbot Green
    Talbot Green is a retail and commercial village in Rhondda Cynon Taf, South Wales, known for its shopping centre and role as a local economic hub.
  • E. Englefield Green
    Englefield Green is a village in Surrey, England, known for its proximity to Runnymede and its large common land.
  • 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: Warlingham Green
Triple: [Warlingham, hasLandmark, Warlingham Green]
Generated description
Warlingham Green is a central village green and focal public space in Warlingham, Surrey, surrounded by local shops, pubs, and community amenities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Warlingham Green
Target entity description: Warlingham Green is a central village green and focal public space in Warlingham, Surrey, surrounded by local shops, pubs, and community amenities.
  • A. Langley Green
    Langley Green is a residential neighbourhood within the town of Crawley in West Sussex, England.
  • B. Southwick Green
    Southwick Green is a central public green and recreational open space in the village of Southwick, West Sussex, England.
  • C. Palmers Green
    Palmers Green is a suburban area in the London Borough of Enfield, known for its residential character and significant Greek and Cypriot community.
  • D. Talbot Green
    Talbot Green is a retail and commercial village in Rhondda Cynon Taf, South Wales, known for its shopping centre and role as a local economic hub.
  • E. Englefield Green
    Englefield Green is a village in Surrey, England, known for its proximity to Runnymede and its large common land.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f65ad788190b68d731b6f516d93 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcd2e08c8190808b58fdabe0c9d3 completed April 5, 2026, 1:37 a.m.
NEDg Description generation batch_69d1bd5820408190a4f5f7ef8b0e14aa completed April 5, 2026, 1:39 a.m.
NED2 Entity disambiguation (via description) batch_69d1bdc0135881909b69814e6cf3741b completed April 5, 2026, 1:41 a.m.
Created at: March 30, 2026, 8:23 p.m.