Triple

T18704859
Position Surface form Disambiguated ID Type / Status
Subject ExampleGen E457342 entity
Predicate hasSubcomponent P25619 FINISHED
Object BigQueryExampleGen — NE NERFINISHED

How this triple was built (3 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: BigQueryExampleGen | Statement: [ExampleGen, hasSubcomponent, BigQueryExampleGen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BigQueryExampleGen
Context triple: [ExampleGen, hasSubcomponent, BigQueryExampleGen]
  • A. 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.
  • 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. Apache Beam
    Apache Beam is an open-source unified programming model for defining and executing batch and streaming data processing pipelines across multiple execution engines.
  • D. 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.
  • E. Bigtable
    Bigtable is Google's distributed, scalable NoSQL database designed to handle massive amounts of structured data with high performance and reliability.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BigQueryExampleGen
Target entity description: BigQueryExampleGen is a TFX ExampleGen component variant that reads training examples directly from Google BigQuery for use in TensorFlow Extended pipelines.
  • A. 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.
  • 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. Apache Beam
    Apache Beam is an open-source unified programming model for defining and executing batch and streaming data processing pipelines across multiple execution engines.
  • D. 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.
  • E. Bigtable
    Bigtable is Google's distributed, scalable NoSQL database designed to handle massive amounts of structured data with high performance and reliability.
  • F. None of above. chosen

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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671665bc8190b9b4a4ce4ec5b2eb completed April 19, 2026, 11:36 p.m.
Created at: April 10, 2026, 11:49 a.m.