Triple
T8610613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LXC |
E203904
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Canonical Ltd. |
E193775
|
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: Canonical Ltd. | Statement: [LXC, developer, Canonical Ltd.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canonical Ltd. Context triple: [LXC, developer, Canonical Ltd.]
-
A.
Canonical Ltd.
chosen
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.
Novell
Novell was a prominent software company best known for its NetWare network operating system and contributions to enterprise networking and Linux technologies.
-
C.
Red Hat
Red Hat is a leading American open-source software company best known for its enterprise Linux distribution and related cloud and middleware solutions.
-
D.
BlackBerry Limited
BlackBerry Limited is a Canadian technology company best known for its pioneering smartphones and secure communications software.
-
E.
Corel Corporation
Corel Corporation is a Canadian software company best known for products like CorelDRAW and WordPerfect.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46ee96ac8190809817c403da2889 |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebbc1d8a08190bbcf7c4cef0fe04d |
completed | April 2, 2026, 6:56 p.m. |
Created at: March 30, 2026, 6:25 p.m.