Triple

T5212498
Position Surface form Disambiguated ID Type / Status
Subject Ännchen von Tharau monument E117665 entity
Predicate owner P347 FINISHED
Object City of Klaipėda E21373 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: City of Klaipėda | Statement: [Ännchen von Tharau monument, owner, City of Klaipėda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Klaipėda
Context triple: [Ännchen von Tharau monument, owner, City of Klaipėda]
  • A. Old Town of Klaipėda
    The Old Town of Klaipėda is the historic center of Lithuania’s port city Klaipėda, known for its preserved German-style architecture, cobbled streets, and cultural landmarks.
  • B. Klaipėda chosen
    Klaipėda is a Lithuanian port city on the Baltic Sea known as the country’s main maritime gateway and a key regional transport and industrial hub.
  • C. Marijampolė
    Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
  • D. Trakai
    Trakai is a historic Lithuanian town famed for its medieval island castle and former status as a political center of the Grand Duchy of Lithuania.
  • E. Kovno
    Kovno is the historical name for Kaunas, a major city in Lithuania that was once part of the Russian Empire and had a significant Jewish community.
  • 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a730e6c8190ae6082da41ee592a completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06b04cd881909e31b4e533dc4ae8 completed March 21, 2026, 8:59 p.m.
Created at: March 20, 2026, 1:47 p.m.