Triple

T15937194
Position Surface form Disambiguated ID Type / Status
Subject Kaisermühlen E386467 entity
Predicate near P350 FINISHED
Object Danube Island E1184441 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: Danube Island | Statement: [Kaisermühlen, near, Danube Island]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danube Island
Context triple: [Kaisermühlen, near, Danube Island]
  • A. Donauinsel chosen
    Donauinsel is a long, narrow artificial island in Vienna’s section of the Danube, known as a major recreational area and flood protection structure.
  • B. Cezi Island
    Cezi Island is one of the principal islands in China’s Zhoushan Archipelago, known for its coastal scenery and maritime activities in the East China Sea.
  • C. Zeleny Island
    Zeleny Island is a small island in the Kuril Islands chain of Russia, notable for its protected natural areas and wildlife habitats.
  • D. Reichenau Island
    Reichenau Island is a UNESCO World Heritage island in Lake Constance, Germany, renowned for its medieval monastic heritage and well-preserved churches.
  • E. Isar River island
    Isar River island is a small island in the Isar River in Munich, Germany, known for hosting major cultural and scientific institutions and providing riverside recreational space.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156ab7f548190b2d1aafa0e6d2c24 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe7455c48190bfad24eb8905426d completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 4:53 a.m.