Triple

T30810706
Position Surface form Disambiguated ID Type / Status
Subject Dunnville, Ontario E784636 entity
Predicate hasLandmark P105 FINISHED
Object Byng Island Conservation Area
Byng Island Conservation Area is a popular natural park in Dunnville, Ontario, known for its camping, boating, fishing, and scenic riverside landscapes along the Grand River.
E1933097 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: Byng Island Conservation Area | Statement: [Dunnville, Ontario, hasLandmark, Byng Island Conservation Area]
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: Byng Island Conservation Area
Triple: [Dunnville, Ontario, hasLandmark, Byng Island Conservation Area]
Generated description
Byng Island Conservation Area is a popular natural park in Dunnville, Ontario, known for its camping, boating, fishing, and scenic riverside landscapes along the Grand River.

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_69f224b4eda48190bd212ce4f3901e56 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69064ad888190ba223c7dc83bc98e completed May 3, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbdfa23c81908a1d98e4db0b94da completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bc6cb6a881909ed7d6cc6f4d697d completed June 10, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a28bd11752881909989925c16498f98 completed June 10, 2026, 1:25 a.m.
Created at: April 29, 2026, 8:43 p.m.