Triple

T36218856
Position Surface form Disambiguated ID Type / Status
Subject George Street, Nottingham E1047777 entity
Predicate near P350 FINISHED
Object Lace Market, Nottingham
Lace Market, Nottingham is a historic district in Nottingham, England, famed for its Victorian lace industry heritage, preserved warehouses, and vibrant mix of bars, restaurants, and creative businesses.
E2173060 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: Lace Market, Nottingham | Statement: [George Street, Nottingham, near, Lace Market, Nottingham]
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: Lace Market, Nottingham
Triple: [George Street, Nottingham, near, Lace Market, Nottingham]
Generated description
Lace Market, Nottingham is a historic district in Nottingham, England, famed for its Victorian lace industry heritage, preserved warehouses, and vibrant mix of bars, restaurants, and creative businesses.

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_69f76e42c878819095c8d19c0267fb87 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b57f05888190a255b55b15f6d79d completed May 3, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39342b6fc881908061908586602e96 completed June 22, 2026, 1:10 p.m.
NEDg Description generation batch_6a39361009b08190b079507172f0bd58 completed June 22, 2026, 1:18 p.m.
NED2 Entity disambiguation (via description) batch_6a3936e5f24c8190b3d506491643b625 completed June 22, 2026, 1:21 p.m.
Created at: May 3, 2026, 4:09 p.m.