Triple

T29461849
Position Surface form Disambiguated ID Type / Status
Subject Swan Street (Manchester) E747258 entity
Predicate locatedIn P40 FINISHED
Object Northern Quarter area of Manchester
The Northern Quarter area of Manchester is a vibrant, bohemian district known for its independent bars, cafes, music venues, street art, and creative industries.
E1868930 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: Northern Quarter area of Manchester | Statement: [Swan Street (Manchester), locatedIn, Northern Quarter area of Manchester]
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: Northern Quarter area of Manchester
Triple: [Swan Street (Manchester), locatedIn, Northern Quarter area of Manchester]
Generated description
The Northern Quarter area of Manchester is a vibrant, bohemian district known for its independent bars, cafes, music venues, street art, and creative industries.

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_69f0bd4125f88190b56104591351619c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66ba3925c81909a03f88f1af602b0 completed May 2, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f11193fc819089d38e02a443747a completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f53de088819084971397f08ca821 completed June 7, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a25f94233508190a175f5e6cb258aff completed June 7, 2026, 11:05 p.m.
Created at: April 28, 2026, 3:50 p.m.