Triple

T3326669
Position Surface form Disambiguated ID Type / Status
Subject Breton Women in the Meadow E69931 entity
Predicate usesCharacteristic P274 FINISHED
Object flat areas of color LITERAL 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: flat areas of color | Statement: [Breton Women in the Meadow, usesCharacteristic, flat areas of color]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesCharacteristic
Context triple: [Breton Women in the Meadow, usesCharacteristic, flat areas of color]
  • A. hasCharacteristic chosen
    Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
  • B. usesCharacter
    Indicates that one entity employs, incorporates, or relies on a particular character (such as a symbol, letter, or persona) in its form, function, or representation.
  • C. equipmentCharacteristic
    Indicates that a specific characteristic, property, or attribute is associated with a piece of equipment.
  • D. ownershipCharacteristic
    Indicates that one entity possesses a particular quality, attribute, or condition specifically in its role as an owner of another entity.
  • E. usesIndicator
    Indicates that one entity employs or relies on another entity as an indicator, signal, or metric for assessment, decision-making, or interpretation.
  • F. None of above.

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_69ad85a1829881908942c14075644d0d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb16dc170819086a63e033e17d8b3 completed March 8, 2026, 5:27 p.m.
PD Predicate disambiguation batch_69ada42a19348190a3862ce02451f4aa completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:12 p.m.