Triple
T21775557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rauma Line |
E537563
|
entity |
| Predicate | crosses |
P416
|
FINISHED |
| Object | Rauma River |
—
|
NE NERFINISHED |
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: Rauma River | Statement: [Rauma Line, crosses, Rauma River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rauma River Context triple: [Rauma Line, crosses, Rauma River]
-
A.
Rauma River
chosen
The Rauma River is a scenic river in Norway renowned for its clear turquoise waters, dramatic valley landscapes, and popularity for salmon fishing and outdoor recreation.
-
B.
Tuskora River
The Tuskora River is a small waterway in western Russia that flows through the city of Kursk.
-
C.
Seinäjoki River
Seinäjoki River is a watercourse in western Finland that flows through and gives its name to the city of Seinäjoki.
-
D.
Raisionjoki river
Raisionjoki river is a small river in southwestern Finland that flows through the town of Raisio before emptying into the Archipelago Sea.
-
E.
Kalajoki River
The Kalajoki River is a watercourse in northern Finland that flows through the town of Ylivieska before emptying into the Gulf of Bothnia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f046291d808190b5111a8d4819909f |
completed | April 28, 2026, 5:31 a.m. |
Created at: April 16, 2026, 6:51 p.m.