Triple

T5128848
Position Surface form Disambiguated ID Type / Status
Subject Wild Isles E115645 entity
Predicate hasEpisode P6968 FINISHED
Object Woodland
Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
 E498189 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: Woodland | Statement: [Wild Isles, hasEpisode, Woodland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Woodland
Context triple: [Wild Isles, hasEpisode, Woodland]
  • A. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • B. Woodland
    Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
  • C. 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.
  • D. Woodlands
    Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
  • E. Woodlands
    Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
  • 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: Woodland
Triple: [Wild Isles, hasEpisode, Woodland]
Generated description
Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Woodland
Target entity description: Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
  • A. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • B. Woodland
    Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
  • C. Woodlands
    Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
  • D. 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.
  • E. Woodlands
    Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
  • 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_69bd444426bc819099ccd23f141e22aa completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7825facc8190b2a6c17216290b5c completed March 20, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfd90a848190a1c78063a437cf3c completed March 21, 2026, 5:05 p.m.
NEDg Description generation batch_69bed21a34f881908c3ef34c0971e7b5 completed March 21, 2026, 5:15 p.m.
NED2 Entity disambiguation (via description) batch_69bed2819f408190adc04c438706bfff completed March 21, 2026, 5:16 p.m.
Created at: March 20, 2026, 1:42 p.m.