Triple

T2103605
Position Surface form Disambiguated ID Type / Status
Subject Tisza E37143 entity
Predicate knownAs P39 FINISHED
Object Tisa 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: Tisa | Statement: [Tisza, knownAs, Tisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tisa
Context triple: [Tisza, knownAs, Tisa]
  • A. 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.
  • B. Brda River
    The Brda River is a significant river in northern Poland that flows through the city of Bydgoszcz and is known for its scenic landscapes and recreational opportunities.
  • C. Dunajec River
    The Dunajec River is a picturesque river in southern Poland and northern Slovakia, renowned for its scenic gorge and popular rafting routes through the Pieniny Mountains.
  • D. Körös
    Körös is a river in Central Europe that flows through eastern Hungary and parts of Romania before joining the Tisza River.
  • E. Zala River
    The Zala River is a major river in western Hungary that drains a large catchment area before emptying into Lake Balaton.
  • 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_69ae652fc57881908eaec85edfebeb15 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:43 p.m.