Triple

T27461706
Position Surface form Disambiguated ID Type / Status
Subject Jane Drew E692763 entity
Predicate employer P7 FINISHED
Object Fry, Drew and Partners
Fry, Drew and Partners was a prominent mid-20th-century British architectural practice co-founded by Jane Drew and Maxwell Fry, known for its modernist and socially oriented designs in the UK and abroad.
E1774908 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: Fry, Drew and Partners | Statement: [Jane Drew, employer, Fry, Drew and Partners]
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: Fry, Drew and Partners
Triple: [Jane Drew, employer, Fry, Drew and Partners]
Generated description
Fry, Drew and Partners was a prominent mid-20th-century British architectural practice co-founded by Jane Drew and Maxwell Fry, known for its modernist and socially oriented designs in the UK and abroad.

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_69ef5207903881909427745cda05d27a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62dfa4f3881908a45c137df7fa0db completed May 2, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbda67c0819085a85473ce39dfc1 completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bc906eb481908d12f171b1230dbe completed May 24, 2026, 8:53 a.m.
NED2 Entity disambiguation (via description) batch_6a12bd38f1948190a0b1f05ff28d8289 completed May 24, 2026, 8:56 a.m.
Created at: April 27, 2026, 12:50 p.m.