Triple

T9625004
Position Surface form Disambiguated ID Type / Status
Subject King's Royal Rifle Corps E232436 entity
Predicate battleHonour P12198 FINISHED
Object Waterloo E475003 NE FINISHED

How this triple was built (2 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: [King's Royal Rifle Corps, battleHonour, Waterloo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterloo
Context triple: [King's Royal Rifle Corps, battleHonour, 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 chosen
    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.

Provenance (3 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_69ca848793ec8190a93a12383a754dc0 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9afb67c88190aa170716f0033752 completed April 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1797ab3d4819088da04fd5d00386b completed April 4, 2026, 8:50 p.m.
Created at: March 30, 2026, 8:10 p.m.