Triple
T5957895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vilsandi National Park |
E132561
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Saare County |
E133304
|
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: Saare County | Statement: [Vilsandi National Park, locatedIn, Saare County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saare County Context triple: [Vilsandi National Park, locatedIn, Saare County]
-
A.
Saare County
chosen
Saare County is a county in western Estonia that encompasses the islands of Saaremaa and several smaller islands in the Baltic Sea.
-
B.
Lääne County
Lääne County is a coastal administrative region in western Estonia known for its historic town of Haapsalu and its Baltic Sea shoreline.
-
C.
Hiiu County
Hiiu County is an administrative region of Estonia encompassing the island of Hiiumaa and its surrounding islets in the Baltic Sea.
-
D.
Harju County
Harju County is a northern Estonian county on the Gulf of Finland that includes the nation’s capital, Tallinn, and serves as its main political and economic hub.
-
E.
Upson County
Upson County is a county in central Georgia, United States, known for its seat in Thomaston and its mix of rural communities and small-town industry.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c039c48d0c81908e794c52fddf2ca2 |
completed | March 22, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3dd99888190ac3eeef692a7d879 |
completed | March 23, 2026, 6:55 a.m. |
Created at: March 22, 2026, 4:02 p.m.