Triple

T24814460
Position Surface form Disambiguated ID Type / Status
Subject Ontario Highway 622 E620875 entity
Predicate category P87 FINISHED
Object Ontario provincial highways 600–699
Ontario provincial highways 600–699 are a series of secondary, typically lower-traffic numbered routes in Ontario that serve remote, rural, and northern regions of the province.
 E446614 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 provincial highways 600–699 | Statement: [Ontario Highway 622, category, Ontario provincial highways 600–699]
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 provincial highways 600–699
Triple: [Ontario Highway 622, category, Ontario provincial highways 600–699]
Generated description
Ontario provincial highways 600–699 are a series of secondary, typically lower-traffic numbered routes in Ontario that serve remote, rural, and northern regions 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_69e2fabfd4648190bd0e5c7f4dbb6cab completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4220cebe4819096024c54f111dc55 completed May 1, 2026, 3:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c3c190081909ed5d63d658c87ba completed May 22, 2026, 9:05 a.m.
NEDg Description generation batch_6a1020699b3c81908897bc4600b6034c completed May 22, 2026, 9:22 a.m.
NED2 Entity disambiguation (via description) batch_6a10210266fc81908dd98288bc0e22a2 completed May 22, 2026, 9:25 a.m.
Created at: April 18, 2026, 5:01 a.m.