Triple

T19750473
Position Surface form Disambiguated ID Type / Status
Subject Quick BI E474358 entity
Predicate integratesWith P1075 FINISHED
Object Alibaba Cloud RDS E474347 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: Alibaba Cloud RDS | Statement: [Quick BI, integratesWith, Alibaba Cloud RDS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alibaba Cloud RDS
Context triple: [Quick BI, integratesWith, Alibaba Cloud RDS]
  • A. ApsaraDB for RDS chosen
    ApsaraDB for RDS is Alibaba Cloud’s managed relational database service that provides scalable, high-availability SQL databases with automated management and security features.
  • B. Amazon RDS
    Amazon RDS is a managed relational database service by Amazon Web Services that simplifies setup, operation, and scaling of databases in the cloud.
  • C. PolarDB
    PolarDB is a cloud-native relational database service developed by Alibaba Cloud that provides high performance, scalability, and compatibility with popular database engines.
  • D. RDS
    RDS is a Canadian French-language sports television network that broadcasts a wide range of professional and amateur sporting events.
  • E. RDS
    RDS is a Microsoft Windows Server role that enables users to remotely access desktops and applications hosted on centralized 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_69d8e51940a0819087bd2996f98da668 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6529875688190952af476aa5be492 completed April 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07bd62a4948190a18cb92909593839 completed May 16, 2026, 12:42 a.m.
Created at: April 10, 2026, 1:47 p.m.