Triple
T133361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baltic Sea |
E2697
|
entity |
| Predicate | majorPort |
P528
|
FINISHED |
| Object | Gdańsk |
E18213
|
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: Gdańsk | Statement: [Baltic Sea, majorPort, Gdańsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gdańsk Context triple: [Baltic Sea, majorPort, Gdańsk]
-
A.
Gdańsk
chosen
Gdańsk is a major Polish port city on the Baltic Sea, known for its rich Hanseatic history, shipyards, and role in the origins of the Solidarity movement.
-
B.
Gdynia
Gdynia is a major seaport city on Poland’s Baltic coast, developed rapidly in the 20th century into one of the country’s key maritime and economic centers.
-
C.
Poznań
Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
-
D.
Wrocław
Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
-
E.
Warsaw
Warsaw is the capital and largest city of Poland, known for its resilient history, especially its near-total destruction in World War II and subsequent postwar reconstruction.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25788b2688190a45b39447f702551 |
completed | Feb. 28, 2026, 2:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a338e55004819096a8cc1bfec7a225 |
completed | Feb. 28, 2026, 6:50 p.m. |
Created at: Feb. 28, 2026, 2:30 a.m.