Triple

T26423999
Position Surface form Disambiguated ID Type / Status
Subject British Studio Ceramics E664319 entity
Predicate hasKeyFigure P810 FINISHED
Object Ruth Duckworth
Ruth Duckworth was a German-born British sculptor renowned for her modernist, abstract ceramic and stoneware works that helped redefine studio ceramics in the 20th century.
E1730357 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: Ruth Duckworth | Statement: [British Studio Ceramics, hasKeyFigure, Ruth Duckworth]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ruth Duckworth
Triple: [British Studio Ceramics, hasKeyFigure, Ruth Duckworth]
Generated description
Ruth Duckworth was a German-born British sculptor renowned for her modernist, abstract ceramic and stoneware works that helped redefine studio ceramics in the 20th century.

Provenance (5 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_69ee883ad6a4819088f918e76122d690 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f611b854b8819082ad4a3510a0eb65 completed May 2, 2026, 3:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7fff1548190bf39b5b1b1c2ece5 completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11c88b80d08190b2b52b1f347d4eb2 completed May 23, 2026, 3:32 p.m.
NED2 Entity disambiguation (via description) batch_6a11c901b7c48190a86f5989c70ab615 completed May 23, 2026, 3:34 p.m.
Created at: April 26, 2026, 11:45 p.m.