Triple

T38531557
Position Surface form Disambiguated ID Type / Status
Subject Bowron Lake Provincial Park E923378 entity
Predicate hasMainWaterBody P85029 FINISHED
Object Babcock Lake
Babcock Lake is a freshwater lake located within Bowron Lake Provincial Park in British Columbia, Canada, known as part of the park’s interconnected canoe circuit.
E2292356 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: Babcock Lake | Statement: [Bowron Lake Provincial Park, hasMainWaterBody, Babcock Lake]
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: Babcock Lake
Triple: [Bowron Lake Provincial Park, hasMainWaterBody, Babcock Lake]
Generated description
Babcock Lake is a freshwater lake located within Bowron Lake Provincial Park in British Columbia, Canada, known as part of the park’s interconnected canoe circuit.

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_69f76ea8f6348190a5c03fb6292bbee3 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd2b8f2d081908a44bbadbdc2240a completed May 7, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a683bcfecb48190bb8d865a5f3830f8 completed July 28, 2026, 5:19 a.m.
NEDg Description generation batch_6a683d1371a081909da8bc92abc65b7b completed July 28, 2026, 5:24 a.m.
NED2 Entity disambiguation (via description) batch_6a685f4046b48190bd9a2eb54b90b518 completed July 28, 2026, 7:50 a.m.
Created at: May 3, 2026, 4:32 p.m.