Triple

T20644878
Position Surface form Disambiguated ID Type / Status
Subject Gmunden District E507327 entity
Predicate containsMunicipality P852 FINISHED
Object Tiefgraben 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: Tiefgraben | Statement: [Gmunden District, containsMunicipality, Tiefgraben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiefgraben
Context triple: [Gmunden District, containsMunicipality, Tiefgraben]
  • A. Tiefgraben chosen
    Tiefgraben is a municipality in the Austrian state of Upper Austria, known for its scenic lakeside setting near Mondsee.
  • B. Malita Graben
    Malita Graben is a structural depression and hydrocarbon-bearing sub-basin within the offshore Bonaparte Basin of northern Australia.
  • C. Graben
    Graben is a famous and historic pedestrian street in the center of Vienna, Austria, known for its upscale shops, cafes, and notable Baroque monuments.
  • D. Graben
    Graben is a municipality in the Augsburg district of Bavaria, Germany, known for its location in the Swabian region near the city of Augsburg.
  • E. Graben
    Graben is a small municipality in the Oberaargau region of the canton of Bern in Switzerland.
  • 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_69e0b4be702c8190a3d2410a881d310a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af1dd79481909de985d03ab861c2 completed April 20, 2026, 10:56 p.m.
Created at: April 16, 2026, 11:43 a.m.