Triple

T7932355
Position Surface form Disambiguated ID Type / Status
Subject Cloud Spanner E184215 entity
Predicate integratesWith P1075 FINISHED
Object Pub/Sub E97116 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: Pub/Sub | Statement: [Cloud Spanner, integratesWith, Pub/Sub]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pub/Sub
Context triple: [Cloud Spanner, integratesWith, Pub/Sub]
  • A. Google Cloud Pub/Sub chosen
    Google Cloud Pub/Sub is a fully managed real-time messaging service that enables asynchronous, scalable communication between independent applications and services.
  • B. Pub/Sub Lite
    Pub/Sub Lite is a lower-cost, high-throughput messaging service on Google Cloud designed for streaming data workloads that can tolerate more operational management compared to standard Pub/Sub.
  • C. Publish–Subscribe pattern
    The Publish–Subscribe pattern is a messaging design pattern in which senders (publishers) broadcast messages without knowledge of specific receivers, and subscribers receive only the messages they have expressed interest in.
  • D. Pusher
    Pusher is a 1996 Danish crime thriller film directed by Nicolas Winding Refn that launched Mads Mikkelsen’s film career and became a cult classic.
  • E. Pusher
    Pusher is a TensorFlow Extended (TFX) component responsible for validating and deploying trained machine learning models to serving infrastructure.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3ace87f081908635769942645e78 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c041e588190bfbf251ed88d5bcd completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:08 p.m.