Triple
T7036239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livonia |
E163391
|
entity |
| Predicate | majorCity |
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: [Livonia, majorCity, Tallinn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tallinn Context triple: [Livonia, majorCity, 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.
Maardu
Maardu is an industrial town in northern Estonia, located just east of the capital Tallinn in Harju County.
-
E.
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.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e220508c8190b8950cf38280b8c2 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7943fe4fc819087bbcc724deed80a |
completed | March 28, 2026, 8:41 a.m. |
Created at: March 27, 2026, 2:36 p.m.