Triple

T14926968
Position Surface form Disambiguated ID Type / Status
Subject PIR E372157 entity
Predicate associatedTown P847 FINISHED
Object Pirna E76192 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: Pirna | Statement: [PIR, associatedTown, Pirna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pirna
Context triple: [PIR, associatedTown, Pirna]
  • A. Pirna chosen
    Pirna is a historic town in eastern Germany situated on the River Elbe, known as a gateway to the Saxon Switzerland National Park.
  • B. Velké Poříčí
    Velké Poříčí is a municipality and village in the Hradec Králové Region of the Czech Republic, situated near the town of Náchod close to the Polish border.
  • C. Orlice
    Orlice is a river in the Czech Republic that flows through the city of Hradec Králové and is a tributary of the Labe (Elbe) River.
  • D. Jauru
    Jauru is an alternative name for the Yawuru, an Aboriginal Australian people traditionally associated with the Broome region of Western Australia.
  • E. Mirow
    Mirow is a small historic town in the Mecklenburg Lake District of northeastern Germany, known for its castle island and connections to the House of Mecklenburg-Strelitz.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded633da0c8190b39f606212e48e71 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dc0fa288190935ddd3ce61f3721 completed May 9, 2026, 2:36 a.m.
Created at: April 10, 2026, 2:35 a.m.