Triple

T30853115
Position Surface form Disambiguated ID Type / Status
Subject Canal Street, Manchester E785838 entity
Predicate near P350 FINISHED
Object Whitworth Street
Whitworth Street is a major thoroughfare in central Manchester, England, known for its historic warehouses, proximity to the city’s canal network, and role in the city’s industrial and cultural heritage.
E2288669 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: Whitworth Street | Statement: [Canal Street, Manchester, near, Whitworth Street]
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: Whitworth Street
Triple: [Canal Street, Manchester, near, Whitworth Street]
Generated description
Whitworth Street is a major thoroughfare in central Manchester, England, known for its historic warehouses, proximity to the city’s canal network, and role in the city’s industrial and cultural heritage.

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_69f224b91c14819084e764832fe67a57 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6917eb3c08190a435aa82aea53809 completed May 3, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5aadc19ee08190a6fd465c12f1f200 completed July 17, 2026, 10:33 p.m.
NEDg Description generation batch_6a5aae33e5ac81909020b9923537a4b4 completed July 17, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_6a5accbc99d08190a195410a57ada903 completed July 18, 2026, 12:45 a.m.
Created at: April 29, 2026, 8:46 p.m.