Triple

T277255
Position Surface form Disambiguated ID Type / Status
Subject SQL E5275 entity
Predicate usedBySystem P8459 FINISHED
Object IBM Db2 E35363 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: IBM Db2 | Statement: [SQL, usedBySystem, IBM Db2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: IBM Db2
Context triple: [SQL, usedBySystem, IBM Db2]
  • A. IBM DB2 chosen
    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.
  • B. IBM WebSphere
    IBM WebSphere is a suite of enterprise middleware and application server software designed to build, deploy, and integrate large-scale Java-based web and business applications.
  • C. Oracle Database
    Oracle Database is a widely used enterprise relational database management system known for its scalability, reliability, and robust support for complex data workloads.
  • D. PostgreSQL
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • E. Siebel
    Siebel is a surname most prominently associated with Jennifer Siebel Newsom, an American documentary filmmaker and the First Partner of California.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a260d0dae48190a2ec98d0186fd792 completed Feb. 28, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69a391525a7081909166884a8ea47ace completed March 1, 2026, 1:07 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.