Triple

T8591884
Position Surface form Disambiguated ID Type / Status
Subject Laitila E203445 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Vehmaa E206571 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: Vehmaa | Statement: [Laitila, hasNeighboringMunicipality, Vehmaa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vehmaa
Context triple: [Laitila, hasNeighboringMunicipality, Vehmaa]
  • A. Vehmaa chosen
    Vehmaa is a small rural municipality in southwestern Finland known for its granite quarries and traditional countryside landscape.
  • B. Vesontio
    Vesontio was the ancient Roman city that later became Besançon, an important urban and military center in the province of Germania Superior.
  • C. Nuijamaa
    Nuijamaa is a village and border crossing point in southeastern Finland, located near the Russian border in the region of South Karelia.
  • D. Vitsa
    Vitsa is a traditional stone-built village in the Zagori region of Epirus, northwestern Greece, known for its preserved architecture and scenic mountain setting.
  • E. Kivimäe
    Kivimäe is a residential subdistrict within the Nõmme district of Tallinn, Estonia, known for its green, suburban character.
  • 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_69ca832a7f108190b4e4f5648abf4aa2 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc466747b88190b752f78f361140cb completed March 31, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8b584088190bc5b8b2785894d82 completed April 2, 2026, 5:34 p.m.
Created at: March 30, 2026, 6:23 p.m.