Triple

T9824827
Position Surface form Disambiguated ID Type / Status
Subject South Central Europe E238628 entity
Predicate hasRiver P165 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: [South Central Europe, hasRiver, Tisza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tisza
Context triple: [South Central Europe, hasRiver, 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. Szamos River
    The Szamos River is a Central European river flowing through Romania and Hungary, known for joining the Tisa River and draining part of the Eastern Carpathians.
  • C. Zala River
    The Zala River is a major river in western Hungary that drains a large catchment area before emptying into Lake Balaton.
  • D. Körös
    Körös is a river in Central Europe that flows through eastern Hungary and parts of Romania before joining the Tisza River.
  • E. Sajó River
    The Sajó River is a waterway in Central Europe, chiefly in present-day Hungary and Slovakia, historically notable as the site of the Mongol victory over the Kingdom of Hungary at the 1241 Battle of Mohi.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3181c688190afea3b27ee392a30 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9333d2e708190b0c8ec679bcb6ade completed April 10, 2026, 5:28 p.m.
Created at: March 30, 2026, 8:31 p.m.