Triple
T15115605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kostroma River |
E361030
|
entity |
| Predicate | hasCityOnBank |
P7935
|
FINISHED |
| Object | Soligalich |
E285306
|
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: Soligalich | Statement: [Kostroma River, hasCityOnBank, Soligalich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soligalich Context triple: [Kostroma River, hasCityOnBank, Soligalich]
-
A.
Soligalich
chosen
Soligalich is a historic Russian town known for its preserved 18th–19th century architecture and location along the Kostroma River in Kostroma Oblast.
-
B.
Kunigal
Kunigal is a town in the Tumakuru district of Karnataka, India, known for its proximity to Markonahalli Dam and its agricultural surroundings.
-
C.
Golymin
Golymin is a village in east-central Poland best known as the site of a significant engagement during the Napoleonic Wars.
-
D.
Dagomys
Dagomys is a coastal resort settlement on the Black Sea in the Sochi area of Krasnodar Krai, Russia, known for its beaches and subtropical climate.
-
E.
Garliava
Garliava is a small town in central Lithuania known as a suburban community near the city of Kaunas.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058f4fb88190a3d446a466aebcf1 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfe3fe0081909d9d3a293373254b |
completed | May 9, 2026, 5:02 a.m. |
Created at: April 10, 2026, 3:05 a.m.