Triple

T22714076
Position Surface form Disambiguated ID Type / Status
Subject Leisi E561678 entity
Predicate hasCountyCapital P43440 FINISHED
Object Kuressaare 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: Kuressaare | Statement: [Leisi, hasCountyCapital, Kuressaare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuressaare
Context triple: [Leisi, hasCountyCapital, Kuressaare]
  • A. Kuressaare chosen
    Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
  • B. Kõrgessaare
    Kõrgessaare is a small settlement on the island of Hiiumaa in western Estonia, known for its coastal location and rural character.
  • C. Ruhnu
    Ruhnu is a small Estonian island in the Gulf of Riga, known for its remote location, traditional wooden lighthouse and church, and unique cultural heritage.
  • D. Haapsalu
    Haapsalu is a small seaside town in western Estonia known for its historic wooden architecture, medieval castle, and traditional seaside resort and spa culture.
  • E. Märjamaa
    Märjamaa is a small borough in western Estonia that serves as a local administrative and service center within Rapla County.
  • 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_69e2454f1348819088d83f420925a5c1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1790bdac88190976c83c9039c9d16 completed April 29, 2026, 3:20 a.m.
Created at: April 17, 2026, 3:18 p.m.