Triple

T35032989
Position Surface form Disambiguated ID Type / Status
Subject City of Clarence E1010827 entity
Predicate hasLandmark P105 FINISHED
Object Clarence Mountain Bike Park
Clarence Mountain Bike Park is a dedicated mountain biking area in the City of Clarence, Tasmania, featuring purpose-built trails and facilities for riders of varying skill levels.
E2123304 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: Clarence Mountain Bike Park | Statement: [City of Clarence, hasLandmark, Clarence Mountain Bike Park]
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: Clarence Mountain Bike Park
Triple: [City of Clarence, hasLandmark, Clarence Mountain Bike Park]
Generated description
Clarence Mountain Bike Park is a dedicated mountain biking area in the City of Clarence, Tasmania, featuring purpose-built trails and facilities for riders of varying skill levels.

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_69f76dcea02c81908542a223f6d5059f completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78549d7fc8190adedcef3282becba completed May 3, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37bd2afc3081909fe8ff973dfd0e11 completed June 21, 2026, 10:30 a.m.
NEDg Description generation batch_6a37bdd99244819093669c98be46f903 completed June 21, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a37bfd6e5a48190b6bcc0b9860ad4bb completed June 21, 2026, 10:41 a.m.
Created at: May 3, 2026, 4:01 p.m.