Triple

T25989558
Position Surface form Disambiguated ID Type / Status
Subject Dorothy Squires E646306 entity
Predicate familyName P18 FINISHED
Object Squires
Squires is a surname most notably associated with Welsh singer Dorothy Squires, a popular vocalist in the mid-20th century.
E1704275 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: Squires | Statement: [Dorothy Squires, familyName, Squires]
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: Squires
Triple: [Dorothy Squires, familyName, Squires]
Generated description
Squires is a surname most notably associated with Welsh singer Dorothy Squires, a popular vocalist in the mid-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_69e77e881fc08190ba1c8dc7e2a07f97 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f605469f7881909fb9d981d79def18 completed May 2, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a110793e7ec8190970434cda08ebd49 completed May 23, 2026, 1:49 a.m.
NEDg Description generation batch_6a11080f37c08190b1e814533c85f8f2 completed May 23, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_6a1108aa194481908986a597992ffbac completed May 23, 2026, 1:53 a.m.
Created at: April 22, 2026, 8:55 a.m.