Triple

T4554383
Position Surface form Disambiguated ID Type / Status
Subject WooCommerce E120445 entity
Predicate integratesWith P1075 FINISHED
Object Gutenberg editor E107978 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: Gutenberg editor | Statement: [WooCommerce, integratesWith, Gutenberg editor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gutenberg editor
Context triple: [WooCommerce, integratesWith, Gutenberg editor]
  • A. Magic Editor
    Magic Editor is an AI-powered photo editing feature on Google Pixel devices that lets users easily reframe, reposition, and enhance elements within their images.
  • B. WordPress
    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.
  • C. Swagger Editor
    Swagger Editor is an open-source, browser-based tool for designing, editing, and validating OpenAPI/Swagger API definitions in YAML or JSON.
  • D. Gutenberg chosen
    Gutenberg is the block-based content editor introduced in WordPress to enable more flexible, visual page and post creation.
  • E. Overleaf
    Overleaf is a cloud-based collaborative LaTeX editing platform that allows users to write, share, and compile documents directly in a web browser.
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd58127ed08190a04962a43afb888b completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc575e3388190ac95b9e0537fb701 completed March 20, 2026, 10:08 p.m.
Created at: March 20, 2026, 1:09 p.m.