Triple

T1634153
Position Surface form Disambiguated ID Type / Status
Subject Google Cloud E35325 entity
Predicate hasComponent P35 FINISHED
Object BigQuery E17670 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: BigQuery | Statement: [Google Cloud, hasComponent, BigQuery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BigQuery
Context triple: [Google Cloud, hasComponent, BigQuery]
  • A. Google BigQuery chosen
    Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
  • B. Data Studio
    Data Studio is Google's free data visualization and business intelligence tool that lets users create interactive, shareable reports and dashboards from multiple data sources.
  • C. Snowflake Data Cloud
    Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
  • D. 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.
  • E. Google Cloud Dataproc
    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.
  • 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.