Triple

T1991991
Position Surface form Disambiguated ID Type / Status
Subject Pickering, Ontario E43270 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Woodlands
Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
 E224297 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: Woodlands | Statement: [Pickering, Ontario, hasNeighbourhood, Woodlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Woodlands
Context triple: [Pickering, Ontario, hasNeighbourhood, Woodlands]
  • A. Woodlands
    Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
  • B. Woodlands
    Woodlands is a residential and commercial town in northern Singapore that serves as a key land border crossing point to Malaysia across the Straits of Johor.
  • C. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • D. Islington Woods
    Islington Woods is a residential neighbourhood in the city of Vaughan, Ontario, known for its green spaces and suburban character.
  • E. Willona Woods
    Willona Woods is a witty, outspoken neighbor and close friend of the Evans family on the 1970s sitcom "Good Times," known for her humor and strong, independent personality.
  • 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: Woodlands
Triple: [Pickering, Ontario, hasNeighbourhood, Woodlands]
Generated description
Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Woodlands
Target entity description: Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
  • A. Woodlands
    Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
  • B. Woodlands
    Woodlands is a residential and commercial town in northern Singapore that serves as a key land border crossing point to Malaysia across the Straits of Johor.
  • C. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • D. Islington Woods
    Islington Woods is a residential neighbourhood in the city of Vaughan, Ontario, known for its green spaces and suburban character.
  • E. Willona Woods
    Willona Woods is a witty, outspoken neighbor and close friend of the Evans family on the 1970s sitcom "Good Times," known for her humor and strong, independent personality.
  • 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_69a88714cf2c819081644be450b8356e completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb846f1c0819081edd8d5eb59adce completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ad7c254819091159c5362e7a293 completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0b63b85c819096fc8ad12ace4d22 completed March 8, 2026, 11:50 p.m.
NED2 Entity disambiguation (via description) batch_69ae0bc55fcc8190bf117ef1328b8a76 completed March 8, 2026, 11:52 p.m.
Created at: March 4, 2026, 7:37 p.m.