Triple

T2103606
Position Surface form Disambiguated ID Type / Status
Subject Tisza E37143 entity
Predicate knownAs P39 FINISHED
Object Tisza River E109194 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 | Statement: [Tisza, knownAs, Tisza River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tisza River
Context triple: [Tisza, knownAs, Tisza River]
  • A. Tisza
    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. Körös
    Körös is a river in Central Europe that flows through eastern Hungary and parts of Romania before joining the Tisza River.
  • D. Tisa River chosen
    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.
  • E. 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.
  • 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_69aef07c3420819097a153052feb1a15 completed March 9, 2026, 4:08 p.m.
Created at: March 4, 2026, 7:43 p.m.