Triple
T16156415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mittelrhein |
E392054
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | St. Goar |
E351914
|
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: St. Goar | Statement: [Mittelrhein, hasTown, St. Goar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. Goar Context triple: [Mittelrhein, hasTown, St. Goar]
-
A.
St. Goar
chosen
St. Goar is a historic town on the Rhine River in Germany, renowned for its medieval castles, riverside scenery, and role within the UNESCO-listed Upper Middle Rhine Valley.
-
B.
St. Goarshausen
St. Goarshausen is a historic town on the Rhine River in Germany, renowned for its dramatic riverside setting, medieval castles, and proximity to the famous Lorelei rock.
-
C.
Waidberg
Waidberg is a wooded hill and recreational area on the outskirts of Zurich, Switzerland, known for its hiking trails, viewpoints, and proximity to the Hönggerberg.
-
D.
Bad Schwalbach
Bad Schwalbach is a spa town in the German state of Hesse, known for its mineral springs and location in the Taunus mountains.
-
E.
Rheingönheim
Rheingönheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e5aa57c8190a9d89dd57e30318f |
completed | April 17, 2026, 11:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7ae46dc81908cba9152a6080c3a |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.