Triple
T2990044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vuoksi River |
E80726
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object |
Svetogorsk
Svetogorsk is a small industrial town in northwestern Russia near the Finnish border, known for its paper mill and location along the Vuoksi River.
|
E316280
|
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: Svetogorsk | Statement: [Vuoksi River, flowsThrough, Svetogorsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Svetogorsk Context triple: [Vuoksi River, flowsThrough, Svetogorsk]
-
A.
Primorsk
Primorsk is a port town in northwestern Russia situated on the coast of the Gulf of Finland in Leningrad Oblast.
-
B.
Starogard Gdański
Starogard Gdański is a historic town in northern Poland that serves as an important local industrial and cultural center in the Kociewie region.
-
C.
Kotelniki
Kotelniki is a Moscow Metro station serving as the southeastern terminus of the Tagansko–Krasnopresnenskaya Line in the town of Kotelniki, just outside Moscow.
-
D.
Łeba
Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
-
E.
Jaro
Jaro is a historic district and former town in Iloilo, Philippines, known for its old churches, ancestral houses, and cultural heritage.
- 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: Svetogorsk Triple: [Vuoksi River, flowsThrough, Svetogorsk]
Generated description
Svetogorsk is a small industrial town in northwestern Russia near the Finnish border, known for its paper mill and location along the Vuoksi River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Svetogorsk Target entity description: Svetogorsk is a small industrial town in northwestern Russia near the Finnish border, known for its paper mill and location along the Vuoksi River.
-
A.
Primorsk
Primorsk is a port town in northwestern Russia situated on the coast of the Gulf of Finland in Leningrad Oblast.
-
B.
Starogard Gdański
Starogard Gdański is a historic town in northern Poland that serves as an important local industrial and cultural center in the Kociewie region.
-
C.
Kotelniki
Kotelniki is a Moscow Metro station serving as the southeastern terminus of the Tagansko–Krasnopresnenskaya Line in the town of Kotelniki, just outside Moscow.
-
D.
Łeba
Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
-
E.
Jaro
Jaro is a historic district and former town in Iloilo, Philippines, known for its old churches, ancestral houses, and cultural heritage.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99de55208190bc56ecbe08638e5a |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b10900bf2481908b7742604c6d75e9 |
completed | March 11, 2026, 6:17 a.m. |
| NEDg | Description generation | batch_69b10bda5d848190af553c5f245b165d |
completed | March 11, 2026, 6:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b10c9198288190a3e3ea7112ea4460 |
completed | March 11, 2026, 6:32 a.m. |
Created at: March 8, 2026, 2:59 p.m.