Triple

T31805867
Position Surface form Disambiguated ID Type / Status
Subject New Road (Oxford) E811867 entity
Predicate runsThrough P416 FINISHED
Object West End of Oxford city centre
The West End of Oxford city centre is a redeveloped urban district known for its mix of transport hubs, modern commercial and residential buildings, and proximity to key city landmarks.
E411319 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: West End of Oxford city centre | Statement: [New Road (Oxford), runsThrough, West End of Oxford city centre]
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: West End of Oxford city centre
Triple: [New Road (Oxford), runsThrough, West End of Oxford city centre]
Generated description
The West End of Oxford city centre is a redeveloped urban district known for its mix of transport hubs, modern commercial and residential buildings, and proximity to key city landmarks.

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_69f348e70d188190b4637c5509f81274 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6acaeb3688190bd3f2ad71790f102 completed May 3, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d6a5f208190a8810c068bbf33d6 completed June 13, 2026, 6:11 p.m.
NEDg Description generation batch_6a2da04474e081908f57c586c1db11e6 completed June 13, 2026, 6:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2e5767b5c08190b6ab769558da4220 completed June 14, 2026, 7:25 a.m.
Created at: April 30, 2026, 11:42 p.m.