Triple

T27649212
Position Surface form Disambiguated ID Type / Status
Subject Far Eastern Lake District E696799 entity
Predicate borders P224 FINISHED
Object Central Lake District
The Central Lake District is a core region of England’s Lake District National Park, renowned for its dramatic fells, scenic valleys, and popular tourist towns such as Ambleside and Grasmere.
E3863 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: Central Lake District | Statement: [Far Eastern Lake District, borders, Central Lake District]
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: Central Lake District
Triple: [Far Eastern Lake District, borders, Central Lake District]
Generated description
The Central Lake District is a core region of England’s Lake District National Park, renowned for its dramatic fells, scenic valleys, and popular tourist towns such as Ambleside and Grasmere.

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_69ef590abd3c8190834d0193bde12007 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f631d34c388190bdeb6f523856fc33 completed May 2, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e44903b481909580fc84f92caabd completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e4fbf9cc8190b5bbff117668f81a completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5e1eafc8190912e291b91690548 completed May 24, 2026, 11:49 a.m.
Created at: April 27, 2026, 2:31 p.m.