Triple
T3547470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Estonian language |
E75030
|
entity |
| Predicate | primaryRegion |
P1103
|
FINISHED |
| Object |
Võru County
Võru County is a rural region in southeastern Estonia known for its distinct South Estonian (Võro) linguistic and cultural heritage.
|
E367591
|
NE FINISHED |
How this triple was built (4 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: Võru County | Statement: [South Estonian language, primaryRegion, Võru County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Võru County Context triple: [South Estonian language, primaryRegion, Võru County]
-
A.
Tartu County
Tartu County is an administrative region in eastern Estonia centered around the university city of Tartu and known for its cultural, educational, and economic significance.
-
B.
Harku Parish
Harku Parish is a rural municipality in northern Estonia, located just west of the capital city Tallinn.
-
C.
Viljandi
Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
-
D.
Kuressaare
Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
-
E.
Viedma
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Võru County Triple: [South Estonian language, primaryRegion, Võru County]
Generated description
Võru County is a rural region in southeastern Estonia known for its distinct South Estonian (Võro) linguistic and cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Võru County Target entity description: Võru County is a rural region in southeastern Estonia known for its distinct South Estonian (Võro) linguistic and cultural heritage.
-
A.
Tartu County
Tartu County is an administrative region in eastern Estonia centered around the university city of Tartu and known for its cultural, educational, and economic significance.
-
B.
Harku Parish
Harku Parish is a rural municipality in northern Estonia, located just west of the capital city Tallinn.
-
C.
Viljandi
Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
-
D.
Kuressaare
Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
-
E.
Viedma
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
- F. None of above. chosen
Provenance (5 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_69ad85d33c6c819081d5ac1df13b5680 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbfd0eb6081908f1380db4cfade87 |
completed | March 8, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38be582308190808274c8a530ce51 |
completed | March 13, 2026, 4 a.m. |
| NEDg | Description generation | batch_69b38c6dbfcc8190897d0c12e8ce4416 |
completed | March 13, 2026, 4:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b38cf9d8188190adb91671d062a6f9 |
completed | March 13, 2026, 4:05 a.m. |
Created at: March 8, 2026, 3:20 p.m.