Triple
T371970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Europe |
E8286
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Tallinn |
E20558
|
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: Tallinn | Statement: [Eastern Europe, hasMajorCity, Tallinn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tallinn Context triple: [Eastern Europe, hasMajorCity, Tallinn]
-
A.
Tallinn
chosen
Tallinn is the capital and largest city of Estonia, a historic Baltic Sea port known for its well-preserved medieval Old Town and strategic maritime location.
-
B.
Tartu
Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
-
C.
Helsinki
Helsinki is the capital and largest city of Finland, known for its coastal location on the Baltic Sea, modern design, and vibrant cultural life.
-
D.
Riga
Riga is the capital and largest city of Latvia, a historic cultural and economic hub on the Baltic Sea known for its Art Nouveau architecture and significant port.
-
E.
Vyborg
Vyborg is a historic port city in northwestern Russia near the Finnish border, known for its medieval castle and long-contested status between Sweden, Finland, and Russia.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec00785481908551fc3571fcca47 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3fe90edc48190a477971920c60918 |
completed | March 1, 2026, 8:53 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.