Triple

T10796014
Position Surface form Disambiguated ID Type / Status
Subject Miesbach district E254707 entity
Predicate contains P35 FINISHED
Object Schliersee E915749 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: Schliersee | Statement: [Miesbach district, contains, Schliersee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schliersee
Context triple: [Miesbach district, contains, Schliersee]
  • A. Schliersee chosen
    Schliersee is a picturesque lake and town in the Bavarian Alps of southern Germany, known for its scenic mountain setting and outdoor recreation.
  • B. Ammersee
    Ammersee is a large glacial lake in southern Germany known for its scenic shores, recreational activities, and proximity to the Alps.
  • C. Tegernsee
    Tegernsee is a picturesque alpine lake in southern Germany renowned for its clear waters, surrounding mountains, and popular spa and resort towns.
  • D. Starnberger See
    Starnberger See is a large, scenic lake in southern Germany known for its affluent lakeside communities, recreational activities, and historical associations with Bavarian royalty.
  • E. Wolfgangsee
    Wolfgangsee is a picturesque alpine lake in Austria renowned for its clear waters, surrounding mountains, and popular lakeside resort towns such as St. Wolfgang and St. Gilgen.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73332dbfc8190904434846957b618 completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69e58a8c67248190be284ddd84f9d8b8 completed April 20, 2026, 2:08 a.m.
Created at: April 8, 2026, 9:17 p.m.