Triple
T13496954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staffelberg |
E320785
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Main River |
E113003
|
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: Main River | Statement: [Staffelberg, near, Main River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Main River Context triple: [Staffelberg, near, Main River]
-
A.
You River
The You River is a tributary waterway in southern China that feeds into the larger Yuan River system.
-
B.
River Main
chosen
The River Main is a major waterway in central Germany that flows through cities such as Frankfurt before joining the Rhine.
-
C.
Kako River
The Kako River is a river in Japan whose name was used for the Imperial Japanese Navy cruiser Kako.
-
D.
Sure river
The Sure river is a Swiss watercourse that drains Lake Sempach and flows through the canton of Lucerne before joining larger river systems.
-
E.
Emme River
The Emme River is a Swiss river flowing through the Emmental region and the Swiss Plateau, known for its picturesque valleys and historical flooding events.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf4e9ca4819083116890a65389f9 |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7464125988190b26390669241cc20 |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:43 p.m.