Triple

T1839135
Position Surface form Disambiguated ID Type / Status
Subject Inn E41132 entity
Predicate partOf P40 FINISHED
Object Danube river system E12683 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: Danube river system | Statement: [Inn, partOf, Danube river system]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danube river system
Context triple: [Inn, partOf, Danube river system]
  • A. Danube chosen
    The Danube is one of Europe's longest and most historically significant rivers, flowing from Germany to the Black Sea and passing through numerous Central and Eastern European countries.
  • B. Tisza
    The Tisza is one of Central Europe's significant rivers, flowing through several countries including Hungary before joining the Danube.
  • C. Maritsa
    Maritsa is a significant river in the Balkans that flows through Bulgaria, Greece, and Turkey before emptying into the Aegean Sea.
  • D. Körös
    Körös is a river in Central Europe that flows through eastern Hungary and parts of Romania before joining the Tisza River.
  • E. Velika Morava
    Velika Morava is a major river in central Serbia formed by the confluence of the West and South Morava, flowing northward before joining the Danube.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03b3eb08190ae68d8476fc89c7f completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8929b30c8190b21f16bcb6225406 completed March 9, 2026, 8:47 a.m.
Created at: March 4, 2026, 7:33 p.m.