Triple

T22400951
Position Surface form Disambiguated ID Type / Status
Subject Municipality of McKellar E553756 entity
Predicate containsWaterBody P1778 FINISHED
Object Armstrong Lake
Armstrong Lake is a freshwater lake located within the rural Municipality of McKellar in Ontario, Canada, known for its natural setting and recreational opportunities.
E2293527 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: Armstrong Lake | Statement: [Municipality of McKellar, containsWaterBody, Armstrong 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: Armstrong Lake
Triple: [Municipality of McKellar, containsWaterBody, Armstrong Lake]
Generated description
Armstrong Lake is a freshwater lake located within the rural Municipality of McKellar in Ontario, Canada, known for its natural setting and recreational opportunities.

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_69e11e4da7048190b4387d422a9a0de5 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f158b39c908190a735aa860d733869 completed April 29, 2026, 1:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7abd269a9881908439c5a9abf26737 completed Aug. 11, 2026, 6:11 a.m.
NEDg Description generation batch_6a7abd6a65188190beaf6fe4cd37c440 completed Aug. 11, 2026, 6:12 a.m.
NED2 Entity disambiguation (via description) batch_6a7abdf31e448190b1b25a23ab3990bd completed Aug. 11, 2026, 6:15 a.m.
Created at: April 16, 2026, 8:46 p.m.