Triple

T17560553
Position Surface form Disambiguated ID Type / Status
Subject PostgreSQL function manager E427685 entity
Predicate interactsWith P3970 FINISHED
Object PostgreSQL planner NE NERFINISHED

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: PostgreSQL planner | Statement: [PostgreSQL function manager, interactsWith, PostgreSQL planner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostgreSQL planner
Context triple: [PostgreSQL function manager, interactsWith, PostgreSQL planner]
  • A. Catalyst query optimizer
    Catalyst query optimizer is the extensible query optimization framework in Apache Spark that analyzes, rewrites, and optimizes logical and physical query plans to improve performance.
  • B. “The Design of Postgres”
    “The Design of Postgres” is a foundational technical paper/book in database systems that presents the architecture, design principles, and innovations behind the Postgres relational database, authored by Michael Stonebraker.
  • C. PL/pgSQL
    PL/pgSQL is PostgreSQL’s procedural extension of SQL that allows writing stored functions and triggers with control structures like variables, loops, and conditionals.
  • D. PostgreSQL
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • E. Soufflé Datalog engine
    Soufflé Datalog engine is a high-performance, open-source Datalog compiler and analysis framework widely used for static program analysis and other logic-based data processing tasks.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PostgreSQL planner
Target entity description: The PostgreSQL planner is the query optimization component of PostgreSQL that transforms parsed SQL statements into efficient execution plans based on statistics and available indexes.
  • A. Catalyst query optimizer
    Catalyst query optimizer is the extensible query optimization framework in Apache Spark that analyzes, rewrites, and optimizes logical and physical query plans to improve performance.
  • B. “The Design of Postgres”
    “The Design of Postgres” is a foundational technical paper/book in database systems that presents the architecture, design principles, and innovations behind the Postgres relational database, authored by Michael Stonebraker.
  • C. PL/pgSQL
    PL/pgSQL is PostgreSQL’s procedural extension of SQL that allows writing stored functions and triggers with control structures like variables, loops, and conditionals.
  • D. PostgreSQL
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • E. Soufflé Datalog engine
    Soufflé Datalog engine is a high-performance, open-source Datalog compiler and analysis framework widely used for static program analysis and other logic-based data processing tasks.
  • F. None of above. chosen

Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e456267e208190a1238fbe1a535bb0 completed April 19, 2026, 4:12 a.m.
Created at: April 10, 2026, 5:50 a.m.