Triple
T11385102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latvian National Library |
E269695
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Vidzeme |
E365504
|
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: Vidzeme | Statement: [Latvian National Library, region, Vidzeme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vidzeme Context triple: [Latvian National Library, region, Vidzeme]
-
A.
Vidzeme
chosen
Vidzeme is a historical region in northern Latvia known for its rich cultural heritage, forests, and role in the development of Latvian national identity.
-
B.
Kurzeme
Kurzeme is a historical and cultural region in western Latvia, known for its Baltic Sea coastline, forests, and traditional Latvian heritage.
-
C.
Ziem
Ziem is the surname of French painter Félix Ziem, known for his 19th-century landscapes and Venetian scenes.
-
D.
Zwedru
Zwedru is a major town in eastern Liberia known as an administrative and commercial center for the surrounding region.
-
E.
Pardais
Pardais is a civil parish in the municipality of Vila Viçosa, in Portugal’s Alentejo region.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7fc378d808190b587a044ede67e1e |
completed | April 9, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58c1d4b188190b83cfad0cc95483e |
completed | April 20, 2026, 2:14 a.m. |
Created at: April 8, 2026, 9:34 p.m.