Triple

T7033277
Position Surface form Disambiguated ID Type / Status
Subject Develop module E163318 entity
Predicate supportsTool P12724 FINISHED
Object Adjustment Brush E30414 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: Adjustment Brush | Statement: [Develop module, supportsTool, Adjustment Brush]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adjustment Brush
Context triple: [Develop module, supportsTool, Adjustment Brush]
  • A. Ken Burns effect
    The Ken Burns effect is a filmmaking and video editing technique that creates motion by slowly panning and zooming over still photographs to add visual interest and narrative emphasis.
  • B. Photo Unblur
    Photo Unblur is a Google Photos feature that uses AI to sharpen and clarify blurry images, improving their overall quality and detail.
  • C. Sharpness Lock
    Sharpness Lock is a key lock structure at the southern end of the Gloucester and Sharpness Canal that connects the canal to the Severn Estuary and enables ships to navigate between them.
  • D. Adobe Lightroom chosen
    Adobe Lightroom is a professional photo editing and management software application widely used by photographers for organizing, enhancing, and sharing digital images.
  • E. Bokeh
    Bokeh is an interactive visualization library for Python that enables the creation of rich, web-ready plots and dashboards from large or streaming datasets.
  • 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.