Triple
T9275056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tartu railway station |
E222924
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Valga |
E789703
|
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: Valga | Statement: [Tartu railway station, connectsTo, Valga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valga Context triple: [Tartu railway station, connectsTo, Valga]
-
A.
Valga
chosen
Valga is a small border town in southern Estonia known for forming a twin city with Valka in Latvia.
-
B.
Vanemuine
Vanemuine is a figure from Estonian mythology, often depicted as a wise old bard or god of music and poetry, symbolizing the nation’s cultural and artistic spirit.
-
C.
Viedma
Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
-
D.
Kallaste
Kallaste is a small Estonian town on the western shore of Lake Peipus, known for its Old Believer Russian community and distinctive sandstone cliffs.
-
E.
Heltermaa
Heltermaa is a small port village on the eastern coast of Hiiumaa Island in Estonia, serving as a key ferry connection to the mainland.
- 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_69ca841ffe208190aa7bcffbef2f8379 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd078a045c8190b2c4d1ec64b932ad |
completed | April 1, 2026, 11:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e379a26c8190be2134fcec120f8e |
completed | April 4, 2026, 10:10 a.m. |
Created at: March 30, 2026, 7:34 p.m.