Triple
T3346813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Council of Ontario Universities |
E70394
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | COU |
E70394
|
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: COU | Statement: [Council of Ontario Universities, abbreviation, COU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: COU Context triple: [Council of Ontario Universities, abbreviation, COU]
-
A.
COU
chosen
COU (Council of Ontario Universities) is a coordinating body that represents and advocates for Ontario’s publicly funded universities.
-
B.
COUR
COUR is the stock ticker symbol for Coursera, a major online learning platform offering courses, certificates, and degrees from universities and companies worldwide.
-
C.
COR
COR is the IATA airport code for Ingeniero Aeronáutico Ambrosio L.V. Taravella International Airport serving Córdoba, Argentina.
-
D.
CU
CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
-
E.
CU
CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
- 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1f4ff888190bf14b9b7fbe9bcee |
completed | March 8, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b32522cbc88190b965087a580d7acf |
completed | March 12, 2026, 8:42 p.m. |
Created at: March 8, 2026, 3:12 p.m.