Triple

T9876200
Position Surface form Disambiguated ID Type / Status
Subject Svitava E240078 entity
Predicate flowsThrough P225 FINISHED
Object Svitavy E381816 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: Svitavy | Statement: [Svitava, flowsThrough, Svitavy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Svitavy
Context triple: [Svitava, flowsThrough, Svitavy]
  • A. Svitavy chosen
    Svitavy is a town in the Czech Republic best known as the birthplace of Oskar Schindler, the industrialist who saved hundreds of Jews during the Holocaust.
  • B. Svatava
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • C. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Broumov
    Broumov is a historic town in northeastern Bohemia, Czech Republic, known for its Benedictine monastery and proximity to the Broumov Walls sandstone rock formations.
  • E. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • 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_69ca84e8a0788190b9061811d50fd554 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3fb58d481908407898912c4b4e9 completed April 2, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3a8c95ca081908ceaa89eef87fbc9 completed April 18, 2026, 3:52 p.m.
Created at: March 30, 2026, 8:37 p.m.