Triple

T26403552
Position Surface form Disambiguated ID Type / Status
Subject Stirling-Rawdon E663767 entity
Predicate roadAccessVia P9041 FINISHED
Object Ontario Highway 14
Ontario Highway 14 was a former provincially maintained highway in Ontario, Canada, that connected several rural communities in the eastern part of the province.
 E1873149 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: Ontario Highway 14 | Statement: [Stirling-Rawdon, roadAccessVia, Ontario Highway 14]
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: Ontario Highway 14
Triple: [Stirling-Rawdon, roadAccessVia, Ontario Highway 14]
Generated description
Ontario Highway 14 was a former provincially maintained highway in Ontario, Canada, that connected several rural communities in the eastern part of the province.

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_69ee883931888190901be96d75ee23cc completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f610f61c5c81909e64c651752952b2 completed May 2, 2026, 2:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260bf2a7908190a85d232c9cd2281d completed June 8, 2026, 12:25 a.m.
NEDg Description generation batch_6a26184352288190aa777cc3a13d8412 completed June 8, 2026, 1:17 a.m.
NED2 Entity disambiguation (via description) batch_6a26189229c08190a9ad8cfafbae2251 completed June 8, 2026, 1:19 a.m.
Created at: April 26, 2026, 11:33 p.m.