Triple

T6651754
Position Surface form Disambiguated ID Type / Status
Subject Nysa Kłodzka E150837 entity
Predicate alsoKnownAs P39 FINISHED
Object Eastern Neisse E246387 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: Eastern Neisse | Statement: [Nysa Kłodzka, alsoKnownAs, Eastern Neisse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eastern Neisse
Context triple: [Nysa Kłodzka, alsoKnownAs, Eastern Neisse]
  • A. Lusatian Neisse chosen
    The Lusatian Neisse is a river in Central Europe that flows through the Czech Republic, Germany, and Poland, forming part of the German–Polish border.
  • B. Neuendorf
    Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
  • C. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • D. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • E. Treuenbrietzen
    Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
  • 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_69c687f2c9508190a60b9aad31d3f358 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b0458fb48190a76d8d1d6273a92b completed March 27, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eefb3b6c8190ba797dc51966e3a5 completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 2:01 p.m.