Triple

T25169986
Position Surface form Disambiguated ID Type / Status
Subject River Hoxne E630295 entity
Predicate locatedIn P40 FINISHED
Object Norfolk–Suffolk region
The Norfolk–Suffolk region is an area of eastern England encompassing parts of the counties of Norfolk and Suffolk, known for its rural landscapes, rivers, and historic market towns.
 E1666617 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: Norfolk–Suffolk region | Statement: [River Hoxne, locatedIn, Norfolk–Suffolk region]
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: Norfolk–Suffolk region
Triple: [River Hoxne, locatedIn, Norfolk–Suffolk region]
Generated description
The Norfolk–Suffolk region is an area of eastern England encompassing parts of the counties of Norfolk and Suffolk, known for its rural landscapes, rivers, and historic market towns.

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_69e75a87c9b88190ab60731902a99750 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46d467e6c8190a328ee6b07aef240 completed May 1, 2026, 9:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d15f23481909c74ca1eb7350219 completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105d875860819084ade4a9bf296627 completed May 22, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_6a105edf54888190a3b77f63eb867749 completed May 22, 2026, 1:49 p.m.
Created at: April 21, 2026, 12:19 p.m.