Triple

T11760438
Position Surface form Disambiguated ID Type / Status
Subject Rod Steiger E279640 entity
Predicate notableWork P4 FINISHED
Object Waterloo
Waterloo is a 1970 epic war film depicting Napoleon Bonaparte’s final defeat, noted for its large-scale battle scenes and Rod Steiger’s portrayal of Napoleon.
E943777 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: [Rod Steiger, notableWork, Waterloo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterloo
Context triple: [Rod Steiger, notableWork, Waterloo]
  • A. 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.
  • B. 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.
  • C. Waterloo
    Waterloo was the original name of the settlement that later became the city of Austin, the capital of Texas.
  • D. Waterloo
    Waterloo is a village in North Lanarkshire, Scotland, forming part of the wider Wishaw area.
  • 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: [Rod Steiger, notableWork, Waterloo]
Generated description
Waterloo is a 1970 epic war film depicting Napoleon Bonaparte’s final defeat, noted for its large-scale battle scenes and Rod Steiger’s portrayal of Napoleon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Waterloo
Target entity description: Waterloo is a 1970 epic war film depicting Napoleon Bonaparte’s final defeat, noted for its large-scale battle scenes and Rod Steiger’s portrayal of Napoleon.
  • A. Waterloo
    Waterloo is a town in present-day Belgium best known as the site of Napoleon Bonaparte’s decisive defeat in 1815, which ended the Napoleonic Wars and reshaped European politics.
  • B. Waterloo
    Waterloo is a 1974 hit single by Swedish pop group ABBA that won the Eurovision Song Contest and became one of their most iconic and internationally successful songs.
  • C. Waterloo
    "Waterloo" is a 1974 pop song by Swedish group ABBA that won the Eurovision Song Contest and became one of their signature international hits.
  • D. Waterloo
    "Waterloo" is the 1974 pop song by Swedish group ABBA that launched their international fame after winning the Eurovision Song Contest.
  • E. Waterloo
    Waterloo is a village in North Lanarkshire, Scotland, forming part of the wider Wishaw area.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a52386708190b744746a2db37495 completed April 10, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a3dfd1081908221c8061931282b completed April 28, 2026, 2:23 a.m.
NEDg Description generation batch_69f03196d1608190999c505e96ce6be7 completed April 28, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_69f05af9ce808190bc6c1ec2cb9903f9 completed April 28, 2026, 7 a.m.
Created at: April 8, 2026, 9:41 p.m.