Triple

T9867239
Position Surface form Disambiguated ID Type / Status
Subject Bavarian Sea E239863 entity
Predicate hasIsland P970 FINISHED
Object Herrenchiemsee E211455 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: Herrenchiemsee | Statement: [Bavarian Sea, hasIsland, Herrenchiemsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herrenchiemsee
Context triple: [Bavarian Sea, hasIsland, Herrenchiemsee]
  • A. Herrenchiemsee Palace chosen
    Herrenchiemsee Palace is a lavish 19th-century royal residence built by King Ludwig II of Bavaria on an island in Chiemsee, modeled after France’s Palace of Versailles.
  • B. Thumsee
    Thumsee is a picturesque alpine lake in Bavaria, Germany, known for its clear waters, surrounding forested hills, and popularity as a local recreation and swimming spot.
  • C. Amalienburg
    Amalienburg is an ornate Rococo hunting lodge and pavilion located in the park of Nymphenburg Palace in Munich, Germany.
  • D. Königsbrunn
    Königsbrunn is a town in Bavaria, Germany, located just south of Augsburg and known as a residential and commercial suburb of the city.
  • E. Forggensee
    Forggensee is a large artificial lake in Bavaria, Germany, popular for boating and scenic views of the surrounding Alps and nearby castles.
  • 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_69ca84e7506c819095cbde4ff16512bb completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3d209ac8190b9bc9ff017a132da completed April 2, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e45add0481909a0416035054a563 completed April 5, 2026, 4:26 a.m.
Created at: March 30, 2026, 8:36 p.m.