Triple

T2894910
Position Surface form Disambiguated ID Type / Status
Subject Lusatia E63913 entity
Predicate majorRiver P165 FINISHED
Object 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: Neisse | Statement: [Lusatia, majorRiver, Neisse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neisse
Context triple: [Lusatia, majorRiver, Neisse]
  • A. Lankwitz
    Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
  • B. 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.
  • C. Riesa
    Riesa is a town in the German state of Saxony, situated on the Elbe River and known historically as an important regional railway and industrial center.
  • D. Schkopau
    Schkopau is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its large chemical industry complex.
  • E. Prenzlau
    Prenzlau is a historic town in northeastern Germany’s Brandenburg region, known for its medieval architecture and role as a regional administrative center.
  • 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_69ab4c45822c8190830c5f2bb97bcfd0 completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe06509808190b673222b9ae3d599 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdbd9a9c8190b1135a4120ac0c6b completed March 14, 2026, 2:53 a.m.
Created at: March 6, 2026, 10:07 p.m.