Triple

T10309600
Position Surface form Disambiguated ID Type / Status
Subject Hajdú-Bihar County E241851 entity
Predicate hasMajorRiver P165 FINISHED
Object Körös River E237331 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: Körös River | Statement: [Hajdú-Bihar County, hasMajorRiver, Körös River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Körös River
Context triple: [Hajdú-Bihar County, hasMajorRiver, Körös River]
  • A. Körös chosen
    Körös is a river in Central Europe that flows through eastern Hungary and parts of Romania before joining the Tisza River.
  • B. Eger River
    The Eger River is a watercourse in Central Europe that flows through parts of Germany and the Czech Republic, serving as a tributary of the Elbe River.
  • 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. Crna River
    The Crna River is a significant river in North Macedonia that flows through the Pelagonia region before joining the Axios (Vardar) River.
  • E. Vouga River
    The Vouga River is a river in central Portugal that flows through the Viseu District before emptying into the Atlantic Ocean near Aveiro.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32a18ac81909b4efd8c1ba3e113 completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d65fc0948190af4356fc9f5004bb completed April 18, 2026, 12:54 a.m.
Created at: April 6, 2026, 11:47 a.m.