Triple

T6668048
Position Surface form Disambiguated ID Type / Status
Subject Kagerplassen E151655 entity
Predicate locatedNear P294 FINISHED
Object Kaag E205057 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: Kaag | Statement: [Kagerplassen, locatedNear, Kaag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaag
Context triple: [Kagerplassen, locatedNear, Kaag]
  • A. Kaag chosen
    Kaag is a small Dutch village in South Holland known for its island setting in the Kagerplassen lake area and its traditional water sports and boating culture.
  • B. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • C. Kogarah
    Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
  • D. Konna
    Konna is a town in central Mali that gained prominence as a strategic battleground during the 2013 conflict between Malian and Islamist forces.
  • E. Kykuit
    Kykuit is a historic Rockefeller family estate and grand mansion known for its architecture, art collections, and landscaped gardens overlooking the Hudson River in New York.
  • 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_69c687f71fc081909dbd45d6377f6045 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b0c4a8e48190aa3b2e41902d2f86 completed March 27, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6ef109f5c8190aa28b5d7aa192e6e completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 2:02 p.m.