Triple

T277249
Position Surface form Disambiguated ID Type / Status
Subject SQL E5275 entity
Predicate usedBySystem P8459 FINISHED
Object MySQL E17668 NE FINISHED

How this triple was built (3 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: [SQL, usedBySystem, MySQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MySQL
Context triple: [SQL, usedBySystem, 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. SQL
    SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
  • C. SQL Server
    SQL Server is Microsoft's enterprise-grade relational database management system used for storing, managing, and analyzing data in a wide range of applications.
  • D. IBM DB2
    IBM DB2 is a family of enterprise-grade relational database management systems developed by IBM, widely used for high-performance, scalable data storage and transaction processing across mainframe, distributed, and cloud environments.
  • E. PostgreSQL
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedBySystem
Context triple: [SQL, usedBySystem, MySQL]
  • A. usedByManufacturer
    Indicates that a manufacturer makes use of a particular resource, component, method, or tool in its production or operational processes.
  • B. usedOn
    Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
  • C. usedByPerson
    Indicates that something (such as an object, tool, or resource) is utilized or employed by a person.
  • D. usedWith
    Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
  • E. usedFor
    Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
  • F. None of above. chosen

Provenance (5 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25ded68c88190b1fc595ce329aeb9 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a391525a7081909166884a8ea47ace completed March 1, 2026, 1:07 a.m.
PD Predicate disambiguation batch_69a25b7480e881909399beccfc7ffb81 completed Feb. 28, 2026, 3:05 a.m.
PDg Predicate description generation batch_69a25c2d94388190aeda17ddd42b4ac9 completed Feb. 28, 2026, 3:08 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.