Triple

T30259553
Position Surface form Disambiguated ID Type / Status
Subject London King’s Cross–Leeds E769448 entity
Predicate partOfCorridor P840 FINISHED
Object London–Yorkshire rail corridor
The London–Yorkshire rail corridor is a major intercity railway route in England linking London with key destinations across Yorkshire, including cities such as Leeds.
E987533 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: London–Yorkshire rail corridor | Statement: [London King’s Cross–Leeds, partOfCorridor, London–Yorkshire rail corridor]
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: London–Yorkshire rail corridor
Triple: [London King’s Cross–Leeds, partOfCorridor, London–Yorkshire rail corridor]
Generated description
The London–Yorkshire rail corridor is a major intercity railway route in England linking London with key destinations across Yorkshire, including cities such as Leeds.

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_69f22484a5f48190b678cd607700bc82 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f680a734788190ae3e75d06552d571 completed May 2, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27645b5a148190b44d63c93812c076 completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a2766016dd08190895ed5102bf1532a completed June 9, 2026, 1:01 a.m.
NED2 Entity disambiguation (via description) batch_6a2766e3b5bc81908ae6c55770c85a3d completed June 9, 2026, 1:05 a.m.
Created at: April 29, 2026, 7:41 p.m.