Triple

T25663001
Position Surface form Disambiguated ID Type / Status
Subject River Wansbeck E643435 entity
Predicate hasBridge P386 FINISHED
Object Morpeth Chantry Bridge
Morpeth Chantry Bridge is a historic stone bridge in Morpeth, Northumberland, notable for its medieval architecture and proximity to the town’s former chantry building.
E1742831 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: Morpeth Chantry Bridge | Statement: [River Wansbeck, hasBridge, Morpeth Chantry Bridge]
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: Morpeth Chantry Bridge
Triple: [River Wansbeck, hasBridge, Morpeth Chantry Bridge]
Generated description
Morpeth Chantry Bridge is a historic stone bridge in Morpeth, Northumberland, notable for its medieval architecture and proximity to the town’s former chantry building.

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_69e77e7e45648190a068ed3faa8016ea completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5faf125388190bf20dd812f1a2632 completed May 2, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1212ff256c819084a6512ccd803c66 completed May 23, 2026, 8:50 p.m.
NEDg Description generation batch_6a121390ba308190aeb986341e7e939a completed May 23, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a1213fdd87481909362a2385d651387 completed May 23, 2026, 8:54 p.m.
Created at: April 21, 2026, 6:57 p.m.