Triple

T543596
Position Surface form Disambiguated ID Type / Status
Subject Danube E12683 entity
Predicate hasTributary P415 FINISHED
Object Tisza E37143 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: Tisza | Statement: [Danube, hasTributary, Tisza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tisza
Context triple: [Danube, hasTributary, Tisza]
  • A. Tisza chosen
    The Tisza is one of Central Europe's significant rivers, flowing through several countries including Hungary before joining the Danube.
  • B. Danube
    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.
  • C. Drava
    The Drava is a major Central European river that flows through countries including Italy, Austria, Slovenia, Croatia, and Hungary before joining the Danube.
  • D. Dunajec River
    The Dunajec River is a picturesque river in southern Poland and northern Slovakia, renowned for its scenic gorge and popular rafting routes through the Pieniny Mountains.
  • E. Poprad River
    The Poprad River is a mountain river in southern Poland and northeastern Slovakia, known for its scenic valley, spa towns, and role as part of the Polish-Slovak border.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a498dea88881908a938fe8f2313bec completed March 1, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69a51f31b5a88190b39b678229ce83a3 completed March 2, 2026, 5:25 a.m.
Created at: March 1, 2026, 7:32 p.m.