Triple

T8713488
Position Surface form Disambiguated ID Type / Status
Subject Ziller E206836 entity
Predicate hasPart P35 FINISHED
Object Zillergrund E501823 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: Zillergrund | Statement: [Ziller, hasPart, Zillergrund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zillergrund
Context triple: [Ziller, hasPart, Zillergrund]
  • A. Tillyschanze
    Tillyschanze is a historic lookout tower and popular viewpoint near Hann. Münden in Lower Saxony, Germany, offering panoramic views over the town and surrounding landscape.
  • B. Sihltal
    Sihltal is a Swiss valley in the canton of Zurich shaped by the Sihl River, known for its scenic landscapes and proximity to the city of Zurich.
  • C. Kaltenbach chosen
    Kaltenbach is a small Austrian village and ski resort town in the Zillertal Valley, known for its access to the Hochzillertal-Hochfügen ski area.
  • D. Reinsberg
    Reinsberg is a municipality in the German state of Saxony, located within the administrative district of Mittelsachsen.
  • E. Bergrheinfeld
    Bergrheinfeld is a municipality in the Schweinfurt district of northern Bavaria, Germany, known for its residential character and proximity to the industrial city of Schweinfurt.
  • 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_69cf28cd239c81909d1feb98b652eb26 completed April 3, 2026, 2:41 a.m.
Created at: March 30, 2026, 6:35 p.m.