Triple
T14156590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Alban-Graben |
E350828
|
entity |
| Predicate | hasNearbyRiver |
P8567
|
FINISHED |
| Object | Rhine |
E13461
|
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: Rhine | Statement: [St. Alban-Graben, hasNearbyRiver, Rhine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rhine Context triple: [St. Alban-Graben, hasNearbyRiver, Rhine]
-
A.
Rhine
chosen
The Rhine is one of Europe's most important rivers, historically serving as a vital trade route and cultural boundary from the Alps through Germany to the North Sea.
-
B.
RHINE
RHINE is a pivotal phase III clinical trial evaluating faricimab for the treatment of diabetic macular edema.
-
C.
High Rhine
The High Rhine is a stretch of the Rhine River in Central Europe, flowing swiftly between Lake Constance and Basel and forming part of the border between Germany and Switzerland.
-
D.
Rhens
Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
-
E.
Lower Rhine
The Lower Rhine is the downstream section of the Rhine River flowing from roughly Bonn through Germany and the Netherlands to the North Sea, known for its dense population, industry, and historical river landscapes.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6135744c81909a43d659f5fe2895 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7cb4d348190962ba5fa21fbb77b |
completed | May 7, 2026, 8:36 p.m. |
Created at: April 10, 2026, 12:58 a.m.