Triple

T26868997
Position Surface form Disambiguated ID Type / Status
Subject Keith Williams Architects E676553 entity
Predicate foundedBy P104 FINISHED
Object Keith Williams
Keith Williams is a British architect best known as the founder and principal of the award-winning practice Keith Williams Architects, recognized for its contemporary civic and cultural buildings.
E1743870 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: Keith Williams | Statement: [Keith Williams Architects, foundedBy, Keith Williams]
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: Keith Williams
Triple: [Keith Williams Architects, foundedBy, Keith Williams]
Generated description
Keith Williams is a British architect best known as the founder and principal of the award-winning practice Keith Williams Architects, recognized for its contemporary civic and cultural buildings.

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_69eee9ba94bc8190b44c5d4397d04ecd completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61e99f138819097659bf61b6b35c2 completed May 2, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12135c0a9481909e4681600ea8ef4d completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a12144d20688190a5a89c747a90c7a1 completed May 23, 2026, 8:55 p.m.
NED2 Entity disambiguation (via description) batch_6a12150ca50881909438084adda62d39 completed May 23, 2026, 8:58 p.m.
Created at: April 27, 2026, 5:30 a.m.