Triple

T8748022
Position Surface form Disambiguated ID Type / Status
Subject Jumbo Water Tower E207880 entity
Predicate nickname P55 FINISHED
Object Jumbo
Jumbo is a prominent historic water tower in Colchester, England, renowned for its massive size and distinctive Victorian brick architecture.
 E755320 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: Jumbo | Statement: [Jumbo Water Tower, nickname, Jumbo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jumbo
Context triple: [Jumbo Water Tower, nickname, Jumbo]
  • A. Jumbo
    Jumbo was the nickname of British Army officer Field Marshal Henry Maitland Wilson, a senior commander during the Second World War.
  • B. Jumbo
    Jumbo is a 1935 Rodgers and Hart Broadway musical comedy best known for its circus setting and elaborate live-animal performances.
  • C. Jumbo
    Jumbo is a prominent mountain peak in New Zealand’s Tararua Range, popular with trampers for its alpine views and access to nearby huts and ridgelines.
  • D. Jumbo
    Jumbo is a major Latin American supermarket and hypermarket chain known for offering a wide range of groceries and household products.
  • E. Jumbo Mark II
    Jumbo Mark II is a class of large, modern car ferries operated by Washington State Ferries for high-capacity passenger and vehicle transport.
  • 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: Jumbo
Triple: [Jumbo Water Tower, nickname, Jumbo]
Generated description
Jumbo is a prominent historic water tower in Colchester, England, renowned for its massive size and distinctive Victorian brick architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jumbo
Target entity description: Jumbo is a prominent historic water tower in Colchester, England, renowned for its massive size and distinctive Victorian brick architecture.
  • A. Jumbo
    Jumbo was the nickname of British Army officer Field Marshal Henry Maitland Wilson, a senior commander during the Second World War.
  • B. Jumbo
    Jumbo is a 1935 Rodgers and Hart Broadway musical comedy best known for its circus setting and elaborate live-animal performances.
  • C. Jumbo
    Jumbo is a prominent mountain peak in New Zealand’s Tararua Range, popular with trampers for its alpine views and access to nearby huts and ridgelines.
  • D. Jumbo
    Jumbo is a major Latin American supermarket and hypermarket chain known for offering a wide range of groceries and household products.
  • E. Jumbo Mark II
    Jumbo Mark II is a class of large, modern car ferries operated by Washington State Ferries for high-capacity passenger and vehicle transport.
  • 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_69ca835bb2bc819084bb5906cb6ef7f8 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5da2d67c819094b2b39c78384d0d completed March 31, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf4313630881909b946cb8a2bdf793 completed April 3, 2026, 4:33 a.m.
NEDg Description generation batch_69cf4462da648190a621397fa88dd4bd completed April 3, 2026, 4:38 a.m.
NED2 Entity disambiguation (via description) batch_69cf454c4d248190a925b15c23af1a24 completed April 3, 2026, 4:42 a.m.
Created at: March 30, 2026, 6:39 p.m.