Triple

T24346297
Position Surface form Disambiguated ID Type / Status
Subject Old Cummer GO Station E613649 entity
Predicate locatedNear P294 FINISHED
Object Old Cummer Avenue
Old Cummer Avenue is a local street in Toronto, Ontario, situated in the North York area and serving the residential neighborhood around Old Cummer GO Station.
E1631617 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: Old Cummer Avenue | Statement: [Old Cummer GO Station, locatedNear, Old Cummer Avenue]
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: Old Cummer Avenue
Triple: [Old Cummer GO Station, locatedNear, Old Cummer Avenue]
Generated description
Old Cummer Avenue is a local street in Toronto, Ontario, situated in the North York area and serving the residential neighborhood around Old Cummer GO Station.

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_69e2d7ddd29481909e7f539a6072bd71 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f2932978b88190afc441a3d4805e5f completed April 29, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd6612e788190ad8f9bdc5271e012 completed May 22, 2026, 4:06 a.m.
NEDg Description generation batch_6a0fd889dc948190b7f36a66be17ca15 completed May 22, 2026, 4:16 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd8e99d58819091ad4bf05fdb101a completed May 22, 2026, 4:17 a.m.
Created at: April 18, 2026, 1:58 a.m.