Triple

T31571936
Position Surface form Disambiguated ID Type / Status
Subject Great Wolf Resorts E805587 entity
Predicate hasCompetitor P1375 FINISHED
Object Wilderness Resort
Wilderness Resort is a large family-oriented waterpark and lodging destination in the Wisconsin Dells area, known for its extensive indoor and outdoor aquatic attractions and resort amenities.
E1968250 NE FINISHED

How this triple was built (2 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: Wilderness Resort | Statement: [Great Wolf Resorts, hasCompetitor, Wilderness Resort]
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: Wilderness Resort
Triple: [Great Wolf Resorts, hasCompetitor, Wilderness Resort]
Generated description
Wilderness Resort is a large family-oriented waterpark and lodging destination in the Wisconsin Dells area, known for its extensive indoor and outdoor aquatic attractions and resort amenities.

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_69f348d2ee94819091918d1789398c29 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a7e83cc08190ac517d4d477f8221 completed May 3, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b2d9d01dc8190b06a7c60a5a4b949 completed June 11, 2026, 9:50 p.m.
NEDg Description generation batch_6a2b2f11454c81908802e1168167fed6 completed June 11, 2026, 9:56 p.m.
NED2 Entity disambiguation (via description) batch_6a2b2f7bbcb88190b49bee8fd8d8bdc3 completed June 11, 2026, 9:58 p.m.
Created at: April 30, 2026, 10:20 p.m.