Triple

T2422706
Position Surface form Disambiguated ID Type / Status
Subject Olt River E53453 entity
Predicate mouth P407 FINISHED
Object Danube River 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 | Statement: [Olt River, mouth, Danube River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danube River
Context triple: [Olt River, mouth, Danube River]
  • 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. Elbe
    The Elbe is one of Central Europe's major rivers, flowing from the Czech Republic through Germany to the North Sea and serving as an important waterway for transport, industry, and agriculture.
  • C. Tisza
    The Tisza is one of Central Europe's significant rivers, flowing through several countries including Hungary before joining the Danube.
  • D. Körös
    Körös is a river in Central Europe that flows through eastern Hungary and parts of Romania before joining the Tisza River.
  • E. Traisen
    Traisen is a river in northeastern Austria that flows through Lower Austria 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc972934481909e05bd6f31162f9d completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf32014c8190aa3cfea010c3bb39 completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:42 p.m.