Triple
T9401548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tartu Art Museum |
E226483
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tartu County |
E222912
|
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: Tartu County | Statement: [Tartu Art Museum, locatedIn, Tartu County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tartu County Context triple: [Tartu Art Museum, locatedIn, Tartu County]
-
A.
Tartu County
chosen
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.
Võru County
Võru County is a rural region in southeastern Estonia known for its distinct South Estonian (Võro) linguistic and cultural heritage.
-
C.
Lääne-Viru County
Lääne-Viru County is a northeastern administrative region of Estonia known for its coastal landscapes, historic manors, and the town of Rakvere.
-
D.
Pärnu County
Pärnu County is an administrative region in southwestern Estonia known for its coastal landscapes and the resort city of Pärnu.
-
E.
Viljandi County
Viljandi County is a rural administrative region in southern Estonia known for its lakes, forests, and historic town of Viljandi.
- 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5157d66c819094c18f680c7093f7 |
completed | April 1, 2026, 5:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e3e1ac348190aec39a41b8b113dc |
completed | April 5, 2026, 4:24 a.m. |
Created at: March 30, 2026, 7:46 p.m.