Triple

T6417605
Position Surface form Disambiguated ID Type / Status
Subject Jasmund National Park E127868 entity
Predicate nearestCity P350 FINISHED
Object Sassnitz E123342 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: Sassnitz | Statement: [Jasmund National Park, nearestCity, Sassnitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sassnitz
Context triple: [Jasmund National Park, nearestCity, Sassnitz]
  • A. Sassnitz chosen
    Sassnitz is a port town on the Baltic Sea coast of Germany, located on the island of Rügen and known as a gateway to nearby national parks and chalk cliffs.
  • B. Ueckermünde
    Ueckermünde is a small historic port town in northeastern Germany on the Szczecin Lagoon, known for its maritime heritage and access to the Baltic Sea.
  • C. Gransee
    Gransee is a small historic town in the German state of Brandenburg, known for its well-preserved medieval architecture and location north of Berlin.
  • D. Warnemünde
    Warnemünde is a seaside district and popular Baltic Sea resort of the German city of Rostock, known for its wide sandy beaches and maritime atmosphere.
  • E. Heringsdorf
    Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
  • 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_69c0083815208190a9b299b8e0640218 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068ea06b08190901e0c0a18fd5170 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640ce3f9481908fa96fb5b2bc8db9 completed March 27, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:42 p.m.