Triple

T17235508
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Environmental, Regional and Educational Sciences E418347 entity
Predicate city P40 FINISHED
Object Graz E91728 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: Graz | Statement: [Faculty of Environmental, Regional and Educational Sciences, city, Graz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graz
Context triple: [Faculty of Environmental, Regional and Educational Sciences, city, Graz]
  • A. Graz chosen
    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.
  • B. Villach
    Villach is a historic city in southern Austria known for its Alpine setting, thermal spas, and role as a regional transport and cultural hub.
  • C. Klagenfurt
    Klagenfurt is the capital city of the Austrian state of Carinthia, known for its historic old town and proximity to Lake Wörthersee.
  • D. St. Pölten
    St. Pölten is the capital city of the Austrian state of Lower Austria, known for its baroque architecture and role as a regional administrative and cultural center.
  • E. Linz
    Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dfb04e481909f4ee3ed31fffe10 completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01676382388190ab82bd10bd53f59e completed May 11, 2026, 5:21 a.m.
Created at: April 10, 2026, 5:39 a.m.