Triple

T2103658
Position Surface form Disambiguated ID Type / Status
Subject Debrecen E37144 entity
Predicate drainageBasin P1559 FINISHED
Object Tisza River basin 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 River basin | Statement: [Debrecen, drainageBasin, Tisza River basin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tisza River basin
Context triple: [Debrecen, drainageBasin, Tisza River basin]
  • A. Tisza chosen
    The Tisza is one of Central Europe's significant rivers, flowing through several countries including Hungary before joining the Danube.
  • B. Zala River
    The Zala River is a major river in western Hungary that drains a large catchment area before emptying into Lake Balaton.
  • C. Tisa River
    The Tisa River is a major Central and Eastern European waterway that flows through countries including Ukraine, Romania, Hungary, Slovakia, and Serbia 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. Bodrog
    Bodrog is a river in Central Europe that flows through Slovakia and Hungary before joining the Tisza River.
  • 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_69a8861828948190924aa30c08806b3a completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abbabf7cdc81909636dff34badc1c5 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69af175e79d881909390ae71cceb6db2 completed March 9, 2026, 6:54 p.m.
Created at: March 4, 2026, 7:43 p.m.