Triple

T21375307
Position Surface form Disambiguated ID Type / Status
Subject Banbury Road E527185 entity
Predicate majorJunctionWith P1018 FINISHED
Object Marston Ferry Road
Marston Ferry Road is a key east–west route in Oxford, England, linking North Oxford to the suburb of Marston and providing access to schools, sports facilities, and residential areas.
E1618143 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: Marston Ferry Road | Statement: [Banbury Road, majorJunctionWith, Marston Ferry Road]
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: Marston Ferry Road
Triple: [Banbury Road, majorJunctionWith, Marston Ferry Road]
Generated description
Marston Ferry Road is a key east–west route in Oxford, England, linking North Oxford to the suburb of Marston and providing access to schools, sports facilities, and residential 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5bb031988190ae587730a2131a50 completed April 26, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0f96184a28819091a1a3930107cc24 completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f96c97c7c8190a735c582a3fc5ec9 completed May 21, 2026, 11:35 p.m.
NED2 Entity disambiguation (via description) batch_6a0f981441b08190a0076042748d92ea completed May 21, 2026, 11:41 p.m.
Created at: April 16, 2026, 5:11 p.m.