Triple

T7933064
Position Surface form Disambiguated ID Type / Status
Subject Cloud Build E184227 entity
Predicate integratesWith P1075 FINISHED
Object Cloud Functions E184210 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: Cloud Functions | Statement: [Cloud Build, integratesWith, Cloud Functions]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cloud Functions
Context triple: [Cloud Build, integratesWith, Cloud Functions]
  • A. Cloud Functions chosen
    Cloud Functions is Google Cloud’s serverless compute platform for running event-driven code without managing servers.
  • B. Cloud Functions for Firebase
    Cloud Functions for Firebase is a serverless compute platform that lets developers run backend code in response to Firebase and HTTP events without managing servers.
  • C. Azure Functions
    Azure Functions is a serverless compute service that lets developers run event-driven code on demand in the cloud without managing infrastructure.
  • D. Cloud Run
    Cloud Run is a fully managed serverless compute platform from Google Cloud that runs containerized applications and APIs that scale automatically on demand.
  • E. Function Compute
    Function Compute is Alibaba Cloud’s serverless computing platform that lets developers run code on demand without managing servers.
  • 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_69cb3acfd2a88190b1a13cd6fdedc272 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbde69b608190a49d93c04c46787d completed April 1, 2026, 6:40 a.m.
Created at: March 30, 2026, 5:08 p.m.