Triple

T30835007
Position Surface form Disambiguated ID Type / Status
Subject Manchester Inner Ring Road area E785334 entity
Predicate roadComponent P36772 FINISHED
Object Fairfield Street
Fairfield Street is a central Manchester roadway known for linking key transport hubs, including Manchester Piccadilly railway station, with the surrounding inner-city network.
E1974888 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: Fairfield Street | Statement: [Manchester Inner Ring Road area, roadComponent, Fairfield 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: Fairfield Street
Triple: [Manchester Inner Ring Road area, roadComponent, Fairfield Street]
Generated description
Fairfield Street is a central Manchester roadway known for linking key transport hubs, including Manchester Piccadilly railway station, with the surrounding inner-city network.

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_69f224b73d8c81908129383bfb397c87 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6913cecbc8190a26e1b3233c0d842 completed May 3, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b848ded3481908d1e3d70b0167d3e completed June 12, 2026, 4:01 a.m.
NEDg Description generation batch_6a2b8de5584c8190afea9b72664e75e5 completed June 12, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_6a2b8f7201dc8190aca36312566296ad completed June 12, 2026, 4:47 a.m.
Created at: April 29, 2026, 8:45 p.m.