Triple

T1641227
Position Surface form Disambiguated ID Type / Status
Subject Bay of Gdańsk E35474 entity
Predicate hasBeach P1922 FINISHED
Object Sopot Beach E77811 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: Sopot Beach | Statement: [Bay of Gdańsk, hasBeach, Sopot Beach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sopot Beach
Context triple: [Bay of Gdańsk, hasBeach, Sopot Beach]
  • A. Słupsk Coast
    Słupsk Coast is a coastal region in northern Poland along the Baltic Sea, known for its sandy beaches, dunes, and seaside resorts.
  • B. Sopot chosen
    Sopot is a Polish Baltic Sea resort city famous for its sandy beaches, long wooden pier, and vibrant spa and nightlife culture.
  • C. Perekop Bay
    Perekop Bay is a shallow inlet of the Black Sea located along the northern coast of Crimea, near the Isthmus of Perekop.
  • D. Morskie Oko
    Morskie Oko is a famous glacial lake in the Tatra Mountains of southern Poland, renowned for its scenic alpine setting and popularity as a hiking destination.
  • E. Jomtien Beach
    Jomtien Beach is a popular, more relaxed seaside area near Pattaya in Thailand, known for its long sandy shoreline, water sports, and family-friendly atmosphere.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a3c883c8190bec1d87ecedf2575 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad609cf8488190ba334bdff2c5e78d completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.