Triple

T2555625
Position Surface form Disambiguated ID Type / Status
Subject Transparent Data Encryption E56723 entity
Predicate isImplementedIn P22535 FINISHED
Object MySQL E17668 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: MySQL | Statement: [Transparent Data Encryption, isImplementedIn, MySQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MySQL
Context triple: [Transparent Data Encryption, isImplementedIn, MySQL]
  • A. MySQL chosen
    MySQL is a widely used open-source relational database management system known for its reliability, performance, and role in powering many web applications and services.
  • B. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • C. MySQL HeatWave
    MySQL HeatWave is a fully managed, in-memory query acceleration and analytics engine integrated with MySQL to deliver high-performance OLTP and OLAP processing on the same database service.
  • D. DB
    DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
  • E. SQL
    SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
  • 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_69ab4a4bfec081908039988ec4c86e28 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd30eec988190810346bb8b6cb489 completed March 7, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5d1ad6b4819097f1d18a12aa2b89 completed March 9, 2026, 11:51 p.m.
Created at: March 6, 2026, 9:48 p.m.