Triple

T1649636
Position Surface form Disambiguated ID Type / Status
Subject Google Sheets E35661 entity
Predicate integratesWith P1075 FINISHED
Object Google 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: Google BigQuery | Statement: [Google Sheets, integratesWith, Google BigQuery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Google BigQuery
Context triple: [Google Sheets, integratesWith, Google 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. Bigtable
    Bigtable is Google's distributed, scalable NoSQL database designed to handle massive amounts of structured data with high performance and reliability.
  • 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. Cloud Spanner
    Cloud Spanner is Google Cloud’s fully managed, horizontally scalable, globally distributed relational database service that offers strong consistency and high availability.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a66b58c819082d38ef1c805cf44 completed March 5, 2026, 4:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad60a73a288190a659e2a1f09ba524 completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:29 p.m.