Triple

T17349439
Position Surface form Disambiguated ID Type / Status
Subject Corridor X E421767 entity
Predicate connectsCountry P1083 FINISHED
Object Slovenia NE ONNED1

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: Slovenia | Statement: [Corridor X, connectsCountry, Slovenia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slovenia
Context triple: [Corridor X, connectsCountry, Slovenia]
  • A. Slovenia chosen
    Slovenia is a Central European country known for its mountains, lakes, and historic cities, and is a member of both the European Union and the Eurozone.
  • B. Croatia
    Croatia is a southeastern European country on the Adriatic Sea, known for its historic coastal cities, thousands of islands, and status as a member of both the European Union and NATO.
  • C. Austria and Slovenia
    Austria and Slovenia are neighboring Central European countries known for their shared Alpine landscapes, historical ties within the former Habsburg realm, and integration within the European Union.
  • D. Tursko
    Tursko is a historical settlement known primarily as the site of the medieval Sack of Tursko.
  • E. Slovakia
    Slovakia is a landlocked Central European country known for its mountainous landscapes, medieval castles, and membership in major international organizations such as the European Union and NATO.
  • 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_69d889d520008190a26917a95bf1c2ea completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a2af5f88190b4c292ca30993b36 completed April 19, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01955658b88190bce3fb2b5738afc6 in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:44 a.m.