Triple

T3525945
Position Surface form Disambiguated ID Type / Status
Subject Drava E74537 entity
Predicate passesThroughRegion P3448 FINISHED
Object Carinthia E108550 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: Carinthia | Statement: [Drava, passesThroughRegion, Carinthia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carinthia
Context triple: [Drava, passesThroughRegion, Carinthia]
  • A. Carinthia chosen
    Carinthia is a mountainous federal state in southern Austria known for its Alpine landscapes, lakes, and outdoor tourism.
  • B. Styria
    Styria is a federal state in southeastern Austria known for its capital Graz, diverse landscapes, and strong industrial and educational sectors.
  • C. Burgenland
    Burgenland is the easternmost and least populous state of Austria, known for its wine regions, flat landscapes, and proximity to Hungary.
  • D. County of Tyrol
    The County of Tyrol was a historic principality in the eastern Alps that became a key territory of the Habsburg Monarchy, encompassing regions of present-day Austria and Italy.
  • E. Tirole
    Tirole is the surname of Jean Tirole, a prominent French economist and Nobel laureate known for his work on industrial organization and regulation.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc6a8d0c819094d38b9c47fb67b4 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bca41a88190b5550b9c1e763092 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:19 p.m.