Triple

T399308
Position Surface form Disambiguated ID Type / Status
Subject Battle of Kollaa E9243 entity
Predicate location P40 FINISHED
Object Kollaa E51168 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: Kollaa | Statement: [Battle of Kollaa, location, Kollaa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kollaa
Context triple: [Battle of Kollaa, location, Kollaa]
  • A. Karinska
    Karinska was a renowned 20th-century costume designer best known for her influential work in ballet and theater, particularly with the New York City Ballet.
  • B. 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.
  • C. Kawki
    Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
  • D. Salla chosen
    Salla is a sparsely populated municipality in northeastern Finland, known for its remote wilderness landscapes and history of territorial changes during the Winter War and World War II.
  • E. Klecko
    Klecko is the surname of former American football defensive lineman Joe Klecko, best known for his standout career with the New York Jets as part of the “New York Sack Exchange.”
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ec8d0ca881909d786e8eed9b6748 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41b4695288190b4a7e67b6a112ca6 completed March 1, 2026, 10:56 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.