Triple
T1821949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markham, Ontario |
E40557
|
entity |
| Predicate | hostsCompanyOffices |
P9342
|
FINISHED |
| Object | IBM Canada |
E1102
|
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: IBM Canada | Statement: [Markham, Ontario, hostsCompanyOffices, IBM Canada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IBM Canada Context triple: [Markham, Ontario, hostsCompanyOffices, IBM Canada]
-
A.
Canonical Ltd.
Canonical Ltd. is a UK-based software company best known as the creator and maintainer of the Ubuntu Linux operating system and related open-source technologies.
-
B.
BlackBerry Limited
BlackBerry Limited is a Canadian technology company best known for its pioneering smartphones and secure communications software.
-
C.
IBM
chosen
IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
-
D.
Bell Canada
Bell Canada is a major Canadian telecommunications company providing phone, internet, and television services nationwide.
-
E.
Alberta Machine Intelligence Institute
The Alberta Machine Intelligence Institute (Amii) is a leading Canadian research institute and innovation hub focused on advancing artificial intelligence and machine learning through academic research, industry collaboration, and talent development.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa662b910c8190b1746730ee09015a |
completed | March 6, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf6526f88190907de68a5344a084 |
completed | March 8, 2026, 6:26 p.m. |
Created at: March 4, 2026, 7:32 p.m.