Triple
T1634157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Google Cloud |
E35325
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Dataproc |
E100303
|
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: Dataproc | Statement: [Google Cloud, hasComponent, Dataproc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dataproc Context triple: [Google Cloud, hasComponent, Dataproc]
-
A.
Google Cloud Dataproc
chosen
Google Cloud Dataproc is a managed cloud service for running Apache Hadoop, Spark, and other big data workloads on scalable, automated clusters in Google Cloud.
-
B.
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for developing and executing batch and streaming data processing pipelines, based on Apache Beam, within the Google Cloud ecosystem.
-
C.
Google BigQuery
Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
-
D.
Google Cloud
Google Cloud is Alphabet Inc.'s cloud computing platform offering infrastructure, platform, and software services for building, deploying, and scaling applications and data solutions.
-
E.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909f86abc8190b0b81310dcd7feed |
completed | March 5, 2026, 4:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58d9db5c819081408977834ad606 |
completed | March 8, 2026, 11:09 a.m. |
Created at: March 4, 2026, 7:28 p.m.