Triple
T18800037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cloud Composer |
E459734
|
entity |
| Predicate | hasVersion |
P455
|
FINISHED |
| Object | Cloud Composer 2 |
—
|
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: Cloud Composer 2 | Statement: [Cloud Composer, hasVersion, Cloud Composer 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cloud Composer 2 Context triple: [Cloud Composer, hasVersion, Cloud Composer 2]
-
A.
Cloud Composer
chosen
Cloud Composer is Google Cloud’s fully managed workflow orchestration service based on Apache Airflow, used to author, schedule, and monitor complex data and pipeline workflows across cloud and on-premises environments.
-
B.
GCP
GCP is a Christian publishing organization that produces curriculum and educational resources for churches and families.
-
C.
Cloud 23
Cloud 23 is a stylish, high-rise cocktail bar in Manchester known for its panoramic city views and upscale atmosphere.
-
D.
Anyscale
Anyscale is a company that builds tools and infrastructure to simplify and scale distributed computing and AI applications in the cloud.
-
E.
Cloud Build
Cloud Build is Google Cloud’s fully managed continuous integration and delivery (CI/CD) service for building, testing, and deploying applications at scale.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02273b481909bc250144a0ace32 |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 10, 2026, 11:53 a.m.