Triple

T12062734
Position Surface form Disambiguated ID Type / Status
Subject Mazury E287213 entity
Predicate hasMajorLake P1025 FINISHED
Object Mamry Lake E803110 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: Mamry Lake | Statement: [Mazury, hasMajorLake, Mamry Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mamry Lake
Context triple: [Mazury, hasMajorLake, Mamry Lake]
  • A. Mamry Lake chosen
    Mamry Lake is one of Poland’s largest and most scenic lakes, renowned for its clear waters, numerous islands, and popularity for sailing and water recreation.
  • B. Dobskie Lake
    Dobskie Lake is a scenic freshwater lake in Poland’s Masurian Lake District, known for its natural beauty and popular recreational activities such as sailing and fishing.
  • C. Mogilno Lake
    Mogilno Lake is a natural lake in central Poland known for bordering the town of Mogilno and supporting local recreation and wildlife.
  • D. Simly Lake
    Simly Lake is a major freshwater reservoir and popular recreational spot located in the Margalla Hills near Islamabad, Pakistan.
  • E. Malta Lake
    Malta Lake is an artificial recreational reservoir in Poznań, Poland, known for its rowing course, leisure facilities, and cultural events.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9043f82248190b05692aa0dc178a8 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a64c8bc8190920c1ed858ea4794 completed May 2, 2026, 2:29 p.m.
Created at: April 8, 2026, 9:48 p.m.