Triple
T12678346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memel River |
E302880
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Nemunas |
E406206
|
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: Nemunas | Statement: [Memel River, alsoKnownAs, Nemunas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nemunas Context triple: [Memel River, alsoKnownAs, Nemunas]
-
A.
Nemunas River
chosen
The Nemunas River is the largest river in Lithuania, flowing through major cities like Kaunas and forming part of the country’s border before emptying into the Curonian Lagoon.
-
B.
Gauja
Gauja is the longest river entirely within Latvia, known for its scenic valley, sandstone cliffs, and the national park that bears its name.
-
C.
Vilnia River
The Vilnia River is a picturesque tributary of the Neris River in Lithuania, flowing through and giving its name to the capital city of Vilnius.
-
D.
Akmena-Danė River
The Akmena-Danė River is a waterway in western Lithuania that flows through the port city of Klaipėda before emptying into the Curonian Lagoon.
-
E.
Daugava River
The Daugava River is a major Eastern European river flowing through Russia, Belarus, and Latvia before emptying into the Baltic Sea.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b1dff48190923290555ece5d89 |
completed | April 10, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671a341288190822fae2469efea09 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:20 p.m.