Triple

T36218843
Position Surface form Disambiguated ID Type / Status
Subject George Street, Nottingham E1047777 entity
Predicate hasConnectingStreet P36837 FINISHED
Object Carlton Street, Nottingham
Carlton Street, Nottingham is a central city street in Nottingham’s historic core, known for its mix of shops, bars, and access to nearby cultural and commercial areas.
E2176252 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: Carlton Street, Nottingham | Statement: [George Street, Nottingham, hasConnectingStreet, Carlton Street, 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: Carlton Street, Nottingham
Triple: [George Street, Nottingham, hasConnectingStreet, Carlton Street, Nottingham]
Generated description
Carlton Street, Nottingham is a central city street in Nottingham’s historic core, known for its mix of shops, bars, and access to nearby cultural and commercial areas.

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_6a396dfc565c8190afa3decee103f5e2 completed June 22, 2026, 5:16 p.m.
NEDg Description generation batch_6a396ff709888190988213e71cbfb62a completed June 22, 2026, 5:25 p.m.
NED2 Entity disambiguation (via description) batch_6a3970784914819086898e230ba5f0f2 completed June 22, 2026, 5:27 p.m.
Created at: May 3, 2026, 4:09 p.m.