Triple

T7033564
Position Surface form Disambiguated ID Type / Status
Subject ColdFusion E163324 entity
Predicate supportsDatabase P11254 FINISHED
Object PostgreSQL E17669 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: PostgreSQL | Statement: [ColdFusion, supportsDatabase, PostgreSQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostgreSQL
Context triple: [ColdFusion, supportsDatabase, PostgreSQL]
  • A. PostgreSQL chosen
    PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
  • B. PostgreSQL documentation
    PostgreSQL documentation is the official, comprehensive reference and user guide for the PostgreSQL relational database system, covering its features, configuration, and extensions.
  • 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. PostGIS
    PostGIS is an open-source spatial database extender that adds robust geographic object support and spatial querying capabilities to PostgreSQL.
  • E. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • 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_69c6885d691c81908cf7d31083113886 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e2118fc88190a0751ca18eafb4a5 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7759c8e408190a7d457e77a44ee26 completed March 28, 2026, 6:30 a.m.
Created at: March 27, 2026, 2:36 p.m.