Triple

T710869
Position Surface form Disambiguated ID Type / Status
Subject Hungary–Austria border E14202 entity
Predicate passesNearLake P17985 FINISHED
Object Fertő Lake E89503 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: Fertő Lake | Statement: [Hungary–Austria border, passesNearLake, Fertő Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fertő Lake
Context triple: [Hungary–Austria border, passesNearLake, Fertő Lake]
  • A. Lake Balaton
    Lake Balaton is a major Central European freshwater lake in western Hungary, renowned as a popular tourist and recreation destination.
  • B. Lake Neusiedl chosen
    Lake Neusiedl is a large, shallow steppe lake in Central Europe renowned for its unique wetland ecosystem, birdlife, and surrounding wine-growing region.
  • C. Großer Wannsee lake
    Großer Wannsee lake is a popular recreational lake in southwestern Berlin, known for its beaches, sailing, and proximity to historically significant sites.
  • D. Lake Tegel
    Lake Tegel is a large lake in the northwest of Berlin, Germany, known for its recreational areas, beaches, and surrounding forests.
  • E. Starnberger See
    Starnberger See is a large, scenic lake in southern Germany known for its affluent lakeside communities, recreational activities, and historical associations with Bavarian royalty.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9a1dcc81908bdb7b960765fde5 completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e39a2d4819086ef9b5fba62a725 completed March 3, 2026, 4:06 a.m.
Created at: March 1, 2026, 7:36 p.m.