Triple

T14198763
Position Surface form Disambiguated ID Type / Status
Subject Marksburg Castle E351908 entity
Predicate GermanName P6492 FINISHED
Object Marksburg E351908 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: Marksburg | Statement: [Marksburg Castle, GermanName, Marksburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marksburg
Context triple: [Marksburg Castle, GermanName, Marksburg]
  • A. Marksburg Castle chosen
    Marksburg Castle is a well-preserved medieval hilltop fortress overlooking the Rhine River in Germany, renowned as one of the few castles in the region never destroyed.
  • B. Marienberg
    Marienberg is a historic mining town in Saxony, Germany, known for its Renaissance-era planned layout and location in the central Ore Mountains.
  • C. Siegenburg
    Siegenburg is a market town and municipality in Lower Bavaria, Germany, known for its rural character and location within the Kelheim district.
  • D. Mühlburg
    Mühlburg is a district of Karlsruhe in the German state of Baden-Württemberg, historically known as the birthplace of automobile pioneer Karl Benz.
  • E. Wechselburg
    Wechselburg is a small municipality in Saxony, Germany, known for its historic Benedictine monastery and scenic location along the Zwickauer Mulde river.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61e30f208190b61c1c7bd3501156 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd194d14008190a74021ff5a3e51d1 completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:04 a.m.