Triple

T9096510
Position Surface form Disambiguated ID Type / Status
Subject Zala River E218034 entity
Predicate hasMouthLocation P1008 FINISHED
Object Keszthely Bay 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: Keszthely Bay | Statement: [Zala River, hasMouthLocation, Keszthely Bay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keszthely Bay
Context triple: [Zala River, hasMouthLocation, Keszthely Bay]
  • A. Hungarian Sea
    The "Hungarian Sea" is a popular nickname for Lake Balaton, Central Europe’s largest lake and a major holiday and recreation destination in Hungary.
  • B. Sárospatak
    Sárospatak is a historic town in northeastern Hungary, renowned for its medieval castle and role as a cultural and educational center in the region.
  • C. Lake Balaton chosen
    Lake Balaton is a major Central European freshwater lake in western Hungary, renowned as a popular tourist and recreation destination.
  • D. Bodrog
    Bodrog is a river in Central Europe that flows through Slovakia and Hungary before joining the Tisza River.
  • E. Balatonalmádi
    Balatonalmádi is a popular Hungarian resort town on the northern shore of Lake Balaton, known for its beaches, holiday facilities, and scenic surroundings.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc96b7d0d48190a3b15f35bef087e3 completed April 1, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d054455e10819095738caf0d5795e2 completed April 3, 2026, 11:59 p.m.
Created at: March 30, 2026, 7:15 p.m.