Triple

T19581323
Position Surface form Disambiguated ID Type / Status
Subject Vanasadam E489991 entity
Predicate connectsTo P845 FINISHED
Object Mariehamn 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: Mariehamn | Statement: [Vanasadam, connectsTo, Mariehamn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mariehamn
Context triple: [Vanasadam, connectsTo, Mariehamn]
  • A. Mariehamn chosen
    Mariehamn is the main town and administrative, cultural, and economic center of the autonomous Åland Islands in the Baltic Sea.
  • B. Tórshavn
    Tórshavn is the capital and largest city of the Faroe Islands, serving as the political, cultural, and economic center of the archipelago.
  • C. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • D. Havnor
    Havnor is the central island and political heart of Earthsea, home to its capital city and the seat of the Archipelago’s rulers in Ursula K. Le Guin’s fantasy series.
  • E. Ålesund
    Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
  • 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e640281b7c8190be44268a58df058f completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:42 p.m.