Triple

T19366125
Position Surface form Disambiguated ID Type / Status
Subject Merania E484405 entity
Predicate hasAlternativeName P39 FINISHED
Object Meran NE NERFINISHED

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: Meran | Statement: [Merania, hasAlternativeName, Meran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meran
Context triple: [Merania, hasAlternativeName, Meran]
  • A. Merano chosen
    Merano is a historic spa and resort town in northern Italy known for its mild climate, Alpine scenery, and blend of Italian and Austrian cultural influences.
  • 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. Mendrisio
    Mendrisio is a district and town in the canton of Ticino in southern Switzerland, known for its historic center and proximity to the Italian border.
  • D. Klagenfurt
    Klagenfurt is the capital city of the Austrian state of Carinthia, known for its historic old town and proximity to Lake Wörthersee.
  • E. Bolzano
    Bolzano was an Italian Zara-class heavy cruiser of the Regia Marina that served during World War II in the Mediterranean Sea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619ac26d4819095836d737b629cf1 completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:35 p.m.