Triple

T8878848
Position Surface form Disambiguated ID Type / Status
Subject Kennington Road E211357 entity
Predicate hasConnectingArea P23990 FINISHED
Object Waterloo E265743 NE FINISHED

How this triple was built (3 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: [Kennington Road, hasConnectingArea, Waterloo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterloo
Context triple: [Kennington Road, hasConnectingArea, Waterloo]
  • A. Waterloo chosen
    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 a mid-sized Canadian city in southwestern Ontario known for its universities, tech industry, and role within the Kitchener–Waterloo metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasConnectingArea
Context triple: [Kennington Road, hasConnectingArea, Waterloo]
  • A. connectsArea
    Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
  • B. hasPortArea
    Indicates that an entity possesses or is associated with a specific port area, typically representing the spatial extent or boundary of its port facilities.
  • C. hasSurfaceConnection
    Indicates that two entities are directly connected or in contact at their surfaces, allowing interaction or continuity between them.
  • D. hasBorderConnection chosen
    Indicates that two regions or entities share a common boundary or are directly connected along a border.
  • E. hasAreaType
    Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
  • F. None of above.

Provenance (4 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_69ca838e78748190934d82db3104f855 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc614ad1908190a77808fcf7f3e531 completed April 1, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfabb87c3481908cf11f2e246f42eb completed April 3, 2026, 11:59 a.m.
PD Predicate disambiguation batch_69cc5c2956788190a311c647b4da17a6 completed March 31, 2026, 11:43 p.m.
Created at: March 30, 2026, 6:52 p.m.