Triple
T18704859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ExampleGen |
E457342
|
entity |
| Predicate | hasSubcomponent |
P25619
|
FINISHED |
| Object |
BigQueryExampleGen
BigQueryExampleGen is a TFX ExampleGen component variant that reads training examples directly from Google BigQuery for use in TensorFlow Extended pipelines.
|
E1338344
|
NE FINISHED |
How this triple was built (4 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.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: BigQueryExampleGen Triple: [ExampleGen, hasSubcomponent, BigQueryExampleGen]
Generated description
BigQueryExampleGen is a TFX ExampleGen component variant that reads training examples directly from Google BigQuery for use in TensorFlow Extended pipelines.
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 (5 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. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b38ab548190b46ecda128e93c9b |
completed | May 14, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_6a052c9486908190a5cdb60f7cb65888 |
completed | May 14, 2026, 1:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052cec9c788190a0c9396b35dd95c0 |
completed | May 14, 2026, 2:01 a.m. |
Created at: April 10, 2026, 11:49 a.m.