Triple

T13626543
Position Surface form Disambiguated ID Type / Status
Subject Northern Iowa E325597 entity
Predicate hasCity P316 FINISHED
Object Waterloo
Waterloo is a city in northeastern Iowa known as an industrial and commercial center along the Cedar River.
 E635878 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: Waterloo | Statement: [Northern Iowa, hasCity, Waterloo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Waterloo
Context triple: [Northern Iowa, hasCity, Waterloo]
  • A. Waterloo
    Waterloo is a major district in central London known for its busy railway station, cultural venues like the Southbank Centre, and proximity to landmarks such as the London Eye and the River Thames.
  • B. Waterloo
    Waterloo was the original name of the settlement that later became the city of Austin, the capital of Texas.
  • C. Waterloo
    Waterloo is a village in North Lanarkshire, Scotland, forming part of the wider Wishaw area.
  • D. Waterloo
    Waterloo is a small village in eastern Nebraska, United States, located along the Elkhorn River just west of Omaha.
  • E. Waterloo
    Waterloo is an inner-city suburb of Sydney, Australia, known for its mix of public housing, industrial heritage, and rapid urban redevelopment.
  • 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: Waterloo
Triple: [Northern Iowa, hasCity, Waterloo]
Generated description
Waterloo is a city in northeastern Iowa known as an industrial and commercial center along the Cedar River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Waterloo
Target entity description: Waterloo is a city in northeastern Iowa known as an industrial and commercial center along the Cedar River.
  • A. Waterloo chosen
    Waterloo is a city in northeastern Iowa that serves as a regional hub for industry, transportation, and education along the Cedar River.
  • B. Waterloo
    Waterloo is a small village in eastern Nebraska, United States, located along the Elkhorn River just west of Omaha.
  • C. Waterloo
    Waterloo is a mid-sized Canadian city in southwestern Ontario known for its universities, tech industry, and role within the Kitchener–Waterloo metropolitan area.
  • D. Waterloo
    Waterloo is a coastal town in the Metropolitan Borough of Sefton, Merseyside, England, known for its stretch of beach and proximity to Liverpool.
  • E. Waterloo
    Waterloo is an inner-city suburb of Sydney, Australia, known for its mix of public housing, industrial heritage, and rapid urban redevelopment.
  • F. None of above.

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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbbe9c72c88190be3d7a3f2e96afbc completed April 12, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77fa6a46881909d381d76d391f5b7 completed May 3, 2026, 5:02 p.m.
NEDg Description generation batch_69f782c41634819096b0939c6c917259 completed May 3, 2026, 5:15 p.m.
NED2 Entity disambiguation (via description) batch_69f78366eca88190be313c3a1b1e23ff completed May 3, 2026, 5:18 p.m.
Created at: April 9, 2026, 9:51 p.m.