Triple

T27154198
Position Surface form Disambiguated ID Type / Status
Subject Hall of Memory E682475 entity
Predicate sculptor P184 FINISHED
Object Albert Toft
Albert Toft was a prominent late 19th- and early 20th-century British sculptor known for his idealist style and numerous public monuments and memorials across the United Kingdom.
E1768497 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: Albert Toft | Statement: [Hall of Memory, sculptor, Albert Toft]
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: Albert Toft
Triple: [Hall of Memory, sculptor, Albert Toft]
Generated description
Albert Toft was a prominent late 19th- and early 20th-century British sculptor known for his idealist style and numerous public monuments and memorials across the United Kingdom.

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_69eefaceb2a08190b9659b7f730629f5 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6250512dc81909b88128fa88eef9a completed May 2, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129c9094a48190839d8876081cd9e4 completed May 24, 2026, 6:37 a.m.
NEDg Description generation batch_6a12a073461c8190a32f6f5c1a6cfd19 completed May 24, 2026, 6:53 a.m.
NED2 Entity disambiguation (via description) batch_6a12a0caf4648190a7f3e1ffa500394f completed May 24, 2026, 6:55 a.m.
Created at: April 27, 2026, 9:15 a.m.