Triple

T7469355
Position Surface form Disambiguated ID Type / Status
Subject Balatonlelle E176466 entity
Predicate locatedOn P40 FINISHED
Object Lake Balaton E31666 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: Lake Balaton | Statement: [Balatonlelle, locatedOn, Lake Balaton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Balaton
Context triple: [Balatonlelle, locatedOn, Lake Balaton]
  • A. Lake Balaton chosen
    Lake Balaton is a major Central European freshwater lake in western Hungary, renowned as a popular tourist and recreation destination.
  • B. Lake Neusiedl
    Lake Neusiedl is a large, shallow steppe lake in Central Europe renowned for its unique wetland ecosystem, birdlife, and surrounding wine-growing region.
  • C. Biogradsko Lake
    Biogradsko Lake is a glacial lake in northeastern Montenegro renowned for its clear waters and surrounding primeval forest within Biogradska Gora National Park.
  • D. Solina Lake
    Solina Lake is a large artificial reservoir in southeastern Poland, renowned for its scenic mountain setting, hydroelectric dam, and popularity as a tourist and water-sports destination.
  • E. Popovo Lake
    Popovo Lake is a prominent glacial lake in Bulgaria, known as one of the largest and most scenic high-altitude lakes in the Pirin Mountains.
  • 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_69c69f223fd88190b4c69b95d7cbeeda completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3f845e081908117783ff1e63e23 completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83475392c8190a51d24e1530c0c83 completed March 28, 2026, 8:05 p.m.
Created at: March 27, 2026, 3:41 p.m.