Triple

T20489004
Position Surface form Disambiguated ID Type / Status
Subject Georg von Dollmann E502686 entity
Predicate hasWorkLocation P1527 FINISHED
Object Chiemsee NE NERFINISHED

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: Chiemsee | Statement: [Georg von Dollmann, hasWorkLocation, Chiemsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chiemsee
Context triple: [Georg von Dollmann, hasWorkLocation, Chiemsee]
  • A. Chiemsee chosen
    Chiemsee is one of Germany’s largest lakes, famed for its scenic Alpine setting and historic islands such as Herrenchiemsee with its royal palace.
  • B. Altmühlsee
    Altmühlsee is an artificial recreational lake in Bavaria, Germany, popular for swimming, sailing, and nature conservation.
  • C. Wörthsee
    Wörthsee is a scenic lake and popular recreational destination in Upper Bavaria, Germany, known for its clear waters and proximity to Munich.
  • D. Tegernsee
    Tegernsee is a picturesque alpine lake in southern Germany renowned for its clear waters, surrounding mountains, and popular spa and resort towns.
  • E. Lake Staffelsee
    Lake Staffelsee is a picturesque lake in Upper Bavaria, Germany, known for its islands, recreational opportunities, and scenic Alpine surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b0373881909dd3e9387f82eab4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69b5d93ec81908259696359090b35 completed April 20, 2026, 9:32 p.m.
Created at: April 16, 2026, 11:34 a.m.