Triple

T35416475
Position Surface form Disambiguated ID Type / Status
Subject Algoma–Manitoulin–Kapuskasing E1023654 entity
Predicate includesCensusSubdivision P138716 FINISHED
Object Opasatika
Opasatika is a small rural community and former township in northeastern Ontario, Canada, situated along the Opasatika River and the Ontario Northland Railway.
E2141034 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: Opasatika | Statement: [Algoma–Manitoulin–Kapuskasing, includesCensusSubdivision, Opasatika]
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: Opasatika
Triple: [Algoma–Manitoulin–Kapuskasing, includesCensusSubdivision, Opasatika]
Generated description
Opasatika is a small rural community and former township in northeastern Ontario, Canada, situated along the Opasatika River and the Ontario Northland Railway.

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_69f76df54bac8190bd0d3b0eb35cda5f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_6a03809b0390819096079bac5444f38b completed May 12, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3836b1a7c881909f93f0ef2f2159e9 completed June 21, 2026, 7:08 p.m.
NEDg Description generation batch_6a383a6b04188190a1ef23a42f2fe7c2 completed June 21, 2026, 7:24 p.m.
NED2 Entity disambiguation (via description) batch_6a383acebb9c8190a7dc924e0c637d36 completed June 21, 2026, 7:26 p.m.
Created at: May 3, 2026, 4:03 p.m.