Triple

T1185269
Position Surface form Disambiguated ID Type / Status
Subject Belle Isle Park E25230 entity
Predicate hasAttraction P105 FINISHED
Object Woodlands
Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
 E135747 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: [Belle Isle Park, hasAttraction, Woodlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Woodlands
Context triple: [Belle Isle Park, hasAttraction, Woodlands]
  • A. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • B. Rumsey Woods
    Rumsey Woods is a wooded area within Buffalo’s historic park and parkway system, known for its natural landscape and recreational green space.
  • C. South Woods
    South Woods is a wooded area within New York City's Central Park known for its naturalistic landscape and tranquil, forest-like setting.
  • D. Greenmeadow
    Greenmeadow is a residential neighbourhood within the town of Cwmbran in South Wales.
  • E. بوستان
    بوستان is a celebrated didactic Persian poem by the medieval poet Saadi of Shiraz, renowned for its moral stories and ethical teachings.
  • 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: [Belle Isle Park, hasAttraction, Woodlands]
Generated description
Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Woodlands
Target entity description: Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
  • A. Woodland
    Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
  • B. Rumsey Woods
    Rumsey Woods is a wooded area within Buffalo’s historic park and parkway system, known for its natural landscape and recreational green space.
  • C. South Woods
    South Woods is a wooded area within New York City's Central Park known for its naturalistic landscape and tranquil, forest-like setting.
  • D. Greenmeadow
    Greenmeadow is a residential neighbourhood within the town of Cwmbran in South Wales.
  • E. بوستان
    بوستان is a celebrated didactic Persian poem by the medieval poet Saadi of Shiraz, renowned for its moral stories and ethical teachings.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd39245881908766c41943dc2752 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f239a288190ae488d11cff8ebf2 completed March 7, 2026, 6:32 p.m.
NEDg Description generation batch_69ac6fea11408190b84d9fc54d4c4917 completed March 7, 2026, 6:35 p.m.
NED2 Entity disambiguation (via description) batch_69ac70592c5c8190a1f86378ec5f70a9 completed March 7, 2026, 6:37 p.m.
Created at: March 1, 2026, 7:45 p.m.