Triple

T27117415
Position Surface form Disambiguated ID Type / Status
Subject E.C. Row Expressway E686888 entity
Predicate connectsTo P845 FINISHED
Object Walker Road
Walker Road is a major north–south arterial street in Windsor, Ontario, serving industrial, commercial, and cross-border traffic and linking key routes including the E.C. Row Expressway.
E2291194 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: Walker Road | Statement: [E.C. Row Expressway, connectsTo, Walker Road]
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: Walker Road
Triple: [E.C. Row Expressway, connectsTo, Walker Road]
Generated description
Walker Road is a major north–south arterial street in Windsor, Ontario, serving industrial, commercial, and cross-border traffic and linking key routes including the E.C. Row Expressway.

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_69ef148c2b588190afc15b529f7af845 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62440351081908f74fef3c86d282a completed May 2, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c3837c5fc8190ab599c0305b430a7 completed July 19, 2026, 2:36 a.m.
NEDg Description generation batch_6a5c38858f248190a89e33517b4e5adf completed July 19, 2026, 2:37 a.m.
NED2 Entity disambiguation (via description) batch_6a5c38de0df881909c04f2dfc83ab224 completed July 19, 2026, 2:39 a.m.
Created at: April 27, 2026, 8:57 a.m.