Triple

T10538877
Position Surface form Disambiguated ID Type / Status
Subject Hornby Dock E248642 entity
Predicate namedAfter P63 FINISHED
Object Hugh Hornby
Hugh Hornby was a notable figure associated with maritime commerce and local development in the Liverpool area, after whom the Hornby Dock was named.
E869913 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: Hugh Hornby | Statement: [Hornby Dock, namedAfter, Hugh Hornby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hugh Hornby
Context triple: [Hornby Dock, namedAfter, Hugh Hornby]
  • A. Danny Hornby
    Danny Hornby is one of the children of British novelist and screenwriter Nick Hornby.
  • B. J. J. Hornby
    J. J. Hornby was a mountaineer known for making the first recorded ascent of the Alpine peak Monte Leone.
  • C. Alan Hartley
    Alan Hartley was a senior British Army officer who served as a prominent commander in British India during the era of the British Raj.
  • D. Nicholas Beauman
    Nicholas Beauman is a British editor and publisher known for championing and reissuing neglected literary works, particularly through the imprint Persephone Books.
  • E. Harold Groves
    Harold Groves was an American economist and politician known for his influential work on tax policy and public finance.
  • 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: Hugh Hornby
Triple: [Hornby Dock, namedAfter, Hugh Hornby]
Generated description
Hugh Hornby was a notable figure associated with maritime commerce and local development in the Liverpool area, after whom the Hornby Dock was named.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hugh Hornby
Target entity description: Hugh Hornby was a notable figure associated with maritime commerce and local development in the Liverpool area, after whom the Hornby Dock was named.
  • A. Danny Hornby
    Danny Hornby is one of the children of British novelist and screenwriter Nick Hornby.
  • B. J. J. Hornby
    J. J. Hornby was a mountaineer known for making the first recorded ascent of the Alpine peak Monte Leone.
  • C. Alan Hartley
    Alan Hartley was a senior British Army officer who served as a prominent commander in British India during the era of the British Raj.
  • D. Nicholas Beauman
    Nicholas Beauman is a British editor and publisher known for championing and reissuing neglected literary works, particularly through the imprint Persephone Books.
  • E. Harold Groves
    Harold Groves was an American economist and politician known for his influential work on tax policy and public finance.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a5730d88190b266a940faf53f65 completed April 7, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90e5b827881909e87651a88976f18 completed April 10, 2026, 2:51 p.m.
NEDg Description generation batch_69d9107f488481908845aef0fdf6d60d completed April 10, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_69d911790010819093fc50952502fd59 completed April 10, 2026, 3:04 p.m.
Created at: April 6, 2026, 12:31 p.m.