Triple
T7001812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Reuss |
E162353
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Wassen |
E425683
|
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: Wassen | Statement: [River Reuss, flowsThrough, Wassen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wassen Context triple: [River Reuss, flowsThrough, Wassen]
-
A.
Wassen
chosen
Wassen is a small Swiss village in the canton of Uri, known for its picturesque church and location along the Gotthard railway and road routes in the central Alps.
-
B.
Nissewaard
Nissewaard is a municipality and town in the western Netherlands, located on the island of Voorne-Putten in the province of South Holland.
-
C.
Woudenberg
Woudenberg is a small Dutch municipality and town located in the central Netherlands.
-
D.
Wassenaar
Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
-
E.
Schwansen
Schwansen is a rural peninsula in northern Germany situated between the Schlei inlet and the Eckernförde Bay in the state of Schleswig-Holstein.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc1115c48190a9363473ae21b6c1 |
completed | March 27, 2026, 7:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775573c84819081f34ab2b14b700a |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:33 p.m.