Triple

T8713120
Position Surface form Disambiguated ID Type / Status
Subject Eibsee E206827 entity
Predicate hasIsland P970 FINISHED
Object Ludwigsinsel E753800 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: Ludwigsinsel | Statement: [Eibsee, hasIsland, Ludwigsinsel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ludwigsinsel
Context triple: [Eibsee, hasIsland, Ludwigsinsel]
  • A. Maximiliansinsel chosen
    Maximiliansinsel is a small, picturesque island located in the alpine Eibsee lake at the foot of Germany’s Zugspitze mountain.
  • B. Luiseninsel
    Luiseninsel is a small island and landscaped area within Berlin’s Großer Tiergarten park, known for its tranquil paths and natural scenery.
  • C. Praterinsel
    Praterinsel is a small island in the Isar River in central Munich, known for its cultural events, historic buildings, and riverside recreation.
  • D. Pfaueninsel
    Pfaueninsel is a small, historic island on the Havel River in Berlin, Germany, known for its romantic landscape park, palace, and free-roaming peacocks.
  • E. Tegeler Insel
    Tegeler Insel is an island located within Lake Tegel in Berlin, Germany, known for its natural setting and recreational surroundings.
  • 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_69ca83572d4881909bef3be2b578d539 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5cd522a88190a32facd86206af66 completed March 31, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42998df88190a6eba28c2efb2030 completed April 3, 2026, 4:31 a.m.
Created at: March 30, 2026, 6:35 p.m.