Triple
T797186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latvia |
E17048
|
entity |
| Predicate | hasMajorRiver |
P165
|
FINISHED |
| Object | Daugava |
E28573
|
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: Daugava | Statement: [Latvia, hasMajorRiver, Daugava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daugava Context triple: [Latvia, hasMajorRiver, Daugava]
-
A.
Daugava River
chosen
The Daugava River is a major Eastern European river flowing through Russia, Belarus, and Latvia before emptying into the Baltic Sea.
-
B.
Neman River
The Neman River is a major river in Eastern Europe that flows through Belarus and Lithuania before emptying into the Baltic Sea.
-
C.
Northern Dvina River
The Northern Dvina River is a major waterway in northwestern Russia that flows into the White Sea and has long served as an important route for trade and transport.
-
D.
Dnieper
The Dnieper is a major Eastern European river that flows through Russia, Belarus, and Ukraine before emptying into the Black Sea.
-
E.
Okhta River
The Okhta River is a tributary waterway in northwestern Russia that flows through Saint Petersburg before joining the Neva River.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7b342888190a344fe81a2c9f33c |
completed | March 1, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1ccd40188190b5c4b9c3dc1f7554 |
completed | March 7, 2026, 12:40 p.m. |
Created at: March 1, 2026, 7:38 p.m.