Triple

T20976182
Position Surface form Disambiguated ID Type / Status
Subject Balatonfűzfő E516630 entity
Predicate isLocatedNear P350 FINISHED
Object Balatonkenese NE NERFINISHED

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: Balatonkenese | Statement: [Balatonfűzfő, isLocatedNear, Balatonkenese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balatonkenese
Context triple: [Balatonfűzfő, isLocatedNear, Balatonkenese]
  • A. Balatonkenese chosen
    Balatonkenese is a small Hungarian town on the northeastern shore of Lake Balaton, known as a lakeside resort and holiday destination.
  • B. Balatonakali
    Balatonakali is a small Hungarian village on the northern shore of Lake Balaton, known for its beaches, vineyards, and lakeside tourism.
  • C. Balatoni út
    Balatoni út is a major road in Budapest, Hungary, that runs through the city’s southern districts and provides access toward Lake Balaton and nearby attractions such as Memento Park (Szoborpark).
  • D. Liskamm
    Liskamm is a prominent and notoriously corniced mountain in the Pennine Alps on the Swiss–Italian border, known for its sharp ridges and challenging climbing conditions.
  • E. Balatonhenye
    Balatonhenye is a small village in western Hungary, situated near Lake Balaton in Veszprém County.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4fee5ac8190875fa9ceba1a5e5e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fba3df2081908c1db5f8610ba43d completed April 21, 2026, 4:23 a.m.
Created at: April 16, 2026, 1:47 p.m.