Triple

T8340128
Position Surface form Disambiguated ID Type / Status
Subject Battle of Mariazell E195888 entity
Predicate location P40 FINISHED
Object Mariazell E344008 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: Mariazell | Statement: [Battle of Mariazell, location, Mariazell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mariazell
Context triple: [Battle of Mariazell, location, Mariazell]
  • A. Mariazell chosen
    Mariazell is a renowned Austrian pilgrimage town in Styria, famous for its basilica and long-standing Catholic religious traditions.
  • B. Klosterneuburg
    Klosterneuburg is an Austrian town near Vienna, known for its historic Augustinian monastery and wine-growing tradition along the Danube River.
  • C. Graz
    Graz is Austria’s second-largest city, known for its well-preserved medieval old town and historic role as a center of science and education.
  • D. Leoben
    Leoben is a historic industrial and university city in the Austrian state of Styria, known especially for its steel industry and mining university.
  • 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_69cb7fd7a3888190b54306ed862aded4 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc7237aa0819092b3679a318223ba completed April 2, 2026, 1:32 a.m.
Created at: March 30, 2026, 5:57 p.m.