Triple
T22444652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SmartOS |
E554834
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Joyent |
—
|
NE NERFINISHED |
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: Joyent | Statement: [SmartOS, developer, Joyent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joyent Context triple: [SmartOS, developer, Joyent]
-
A.
Joyent
chosen
Joyent is a cloud computing and hosting company known for its role in developing and supporting scalable server-side technologies, including the early development of Node.js.
-
B.
Loudcloud
Loudcloud was a pioneering early-2000s cloud and managed hosting company co-founded by Marc Andreessen that later evolved into the software firm Opsware.
-
C.
Rackspace
Rackspace is a cloud computing company known for co-founding and helping develop the OpenStack open-source cloud platform.
-
D.
Pivotal Software
Pivotal Software is a cloud-native platform and services company known for its Pivotal Cloud Foundry product and agile software development tools, originally formed as a spin-off from EMC and VMware.
-
E.
Azul Systems
Azul Systems is a software company specializing in high-performance, scalable Java runtimes and JVM technologies for enterprise applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae517208190924a7968723f55ef |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.