Triple

T3644983
Position Surface form Disambiguated ID Type / Status
Subject River Bure E77275 entity
Predicate connectedWaterbody P23655 FINISHED
Object Salhouse Broad
Salhouse Broad is a picturesque, tree-lined lake in the Norfolk Broads of England, popular for boating, wildlife watching, and peaceful riverside walks.
 E376257 NE FINISHED

How this triple was built (4 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: Salhouse Broad | Statement: [River Bure, connectedWaterbody, Salhouse Broad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Salhouse Broad
Context triple: [River Bure, connectedWaterbody, Salhouse Broad]
  • A. Paul Bransom
    Paul Bransom was an American illustrator and wildlife artist best known for his detailed animal drawings in early 20th-century books and magazines.
  • B. Charles Roane
    Charles Roane is a music producer known for his work on the album "Back to Basics."
  • C. Mark Ellam
    Mark Ellam is a cinematographer known for his work on the film "The Take."
  • D. Ben E. Cabell
    Ben E. Cabell was an American politician who served as mayor of Dallas, Texas, in the early 20th century.
  • E. Nat Pendleton
    Nat Pendleton was an American Olympic wrestler-turned-character actor best known for his comic tough-guy roles in 1930s and 1940s Hollywood films.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Salhouse Broad
Triple: [River Bure, connectedWaterbody, Salhouse Broad]
Generated description
Salhouse Broad is a picturesque, tree-lined lake in the Norfolk Broads of England, popular for boating, wildlife watching, and peaceful riverside walks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Salhouse Broad
Target entity description: Salhouse Broad is a picturesque, tree-lined lake in the Norfolk Broads of England, popular for boating, wildlife watching, and peaceful riverside walks.
  • A. Paul Bransom
    Paul Bransom was an American illustrator and wildlife artist best known for his detailed animal drawings in early 20th-century books and magazines.
  • B. Charles Roane
    Charles Roane is a music producer known for his work on the album "Back to Basics."
  • C. Mark Ellam
    Mark Ellam is a cinematographer known for his work on the film "The Take."
  • D. Ben E. Cabell
    Ben E. Cabell was an American politician who served as mayor of Dallas, Texas, in the early 20th century.
  • E. Nat Pendleton
    Nat Pendleton was an American Olympic wrestler-turned-character actor best known for his comic tough-guy roles in 1930s and 1940s Hollywood films.
  • F. None of above. chosen

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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc35da84c81908950de92ba171fa3 completed March 8, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f35985081909a499f9c1668b589 completed March 13, 2026, 5:53 p.m.
NEDg Description generation batch_69b4520fb96481909f54af01fc4a3bbe completed March 13, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_69b45df65f5c8190a9f25e7da926222a completed March 13, 2026, 6:56 p.m.
Created at: March 8, 2026, 3:24 p.m.