Triple

T6916352
Position Surface form Disambiguated ID Type / Status
Subject Mike Little E160063 entity
Predicate softwareDeveloped P73 FINISHED
Object WordPress E19882 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: WordPress | Statement: [Mike Little, softwareDeveloped, WordPress]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WordPress
Context triple: [Mike Little, softwareDeveloped, WordPress]
  • A. WordPress chosen
    WordPress is a widely used open-source content management system that enables users to create, manage, and publish websites and blogs through a user-friendly, web-based interface.
  • B. WordPress.com
    WordPress.com is a popular hosted blogging and website-building platform that allows users to create and manage websites without needing to run their own server software.
  • C. WordPress Foundation
    The WordPress Foundation is a nonprofit organization that supports and protects the open-source WordPress project and its community.
  • D. WP
    WP is the reporting mark and common abbreviation for the Western Pacific Railroad, a historic American railroad that operated primarily in California and the western United States.
  • E. Drupal
    Drupal is a free, open-source content management framework used to build and manage complex websites and web applications.
  • 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_69c6883ab1008190a07129ff06f625d9 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9dec058819094d1913a1e5218c0 completed March 27, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761800804819082320a03f035f05b completed March 28, 2026, 5:05 a.m.
Created at: March 27, 2026, 2:26 p.m.