Triple

T11853810
Position Surface form Disambiguated ID Type / Status
Subject Kwidzyn E281978 entity
Predicate formerName P65 FINISHED
Object Marienwerder E237940 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: Marienwerder | Statement: [Kwidzyn, formerName, Marienwerder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marienwerder
Context triple: [Kwidzyn, formerName, Marienwerder]
  • A. Marienwerder chosen
    Marienwerder is a historic town in former West Prussia, now known as Kwidzyn in Poland, noted for its medieval architecture and Teutonic Order castle.
  • B. Kolberg
    Kolberg is a historic Baltic Sea port city in present-day Kołobrzeg, Poland, known for its strategic military importance and spa tourism.
  • C. Pillau
    Pillau is a Baltic port town (now Baltiysk in Russia’s Kaliningrad Oblast) historically significant as a major evacuation point for German civilians and troops during the final months of World War II.
  • D. Danzig harbor
    Danzig harbor was the port area of the Free City of Danzig (now Gdańsk, Poland) that played a pivotal role at the outbreak of World War II, notably as the site of the German attack on Westerplatte.
  • E. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a696ee548190800d56c64c339b10 completed April 10, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69f167c9d4e88190bfaadada0450e639 completed April 29, 2026, 2:07 a.m.
Created at: April 8, 2026, 9:43 p.m.