Triple

T20120393
Position Surface form Disambiguated ID Type / Status
Subject Tasovice E490589 entity
Predicate locatedOnRiver P165 FINISHED
Object Dyje River NE NERFINISHED

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: Dyje River | Statement: [Tasovice, locatedOnRiver, Dyje River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dyje River
Context triple: [Tasovice, locatedOnRiver, Dyje River]
  • A. Dyje chosen
    The Dyje is a major river in Central Europe that flows through the Czech Republic and Austria, forming part of their border and contributing significantly to the Morava River basin.
  • B. Qu River
    The Qu River is a tributary waterway in southwestern China that feeds into the larger Jialing River system.
  • C. Amper River
    The Amper River is a Bavarian river that flows through Upper Bavaria, including the district of Freising, before joining the Isar River.
  • D. La Doua
    La Doua is a major university and research campus area in the Lyon metropolitan region, known for hosting several science and engineering institutions.
  • E. Donauquelle
    Donauquelle is the spring in Donaueschingen, Germany traditionally regarded as the source of the Danube River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6673cfaac81909d6216f3e37c2439 completed April 20, 2026, 5:49 p.m.
Created at: April 11, 2026, 11:30 p.m.