Triple

T8338346
Position Surface form Disambiguated ID Type / Status
Subject Styria E195845 entity
Predicate hasCity P316 FINISHED
Object Leoben E397975 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: Leoben | Statement: [Styria, hasCity, Leoben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leoben
Context triple: [Styria, hasCity, Leoben]
  • A. Leoben chosen
    Leoben is a historic industrial and university city in the Austrian state of Styria, known especially for its steel industry and mining university.
  • B. Lustenau
    Lustenau is a large market town in the Austrian state of Vorarlberg, known for its location on the Rhine near the Swiss border and its strong textile industry heritage.
  • C. Oberwart
    Oberwart is a town in eastern Austria known as a regional center with a significant Hungarian-speaking minority and a mix of industrial, commercial, and cultural activities.
  • D. Vöcklabruck
    Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
  • E. Gmunden
    Gmunden is a picturesque town in Upper Austria known for its lakeside setting on the Traunsee and its historic ceramics industry.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd68e348190a7cb8639a263b50f completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc71a9abc8190881ff73c6fe851cd completed April 2, 2026, 1:32 a.m.
Created at: March 30, 2026, 5:57 p.m.