Triple
T3172268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oggersheim |
E66380
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Ludwigshafen am Rhein |
E170906
|
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: Ludwigshafen am Rhein | Statement: [Oggersheim, partOf, Ludwigshafen am Rhein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludwigshafen am Rhein Context triple: [Oggersheim, partOf, Ludwigshafen am Rhein]
-
A.
Ludwigshafen am Rhein
chosen
Ludwigshafen am Rhein is an industrial city in southwestern Germany on the Rhine River, best known as the headquarters of the chemical company BASF.
-
B.
Ingelheim am Rhein
Ingelheim am Rhein is a town in western Germany on the Rhine River, known historically as an imperial residence of Charlemagne and today for its wine production and pharmaceutical industry.
-
C.
Mannheim
Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
-
D.
Koblenz
Koblenz is a historic German city in Rhineland-Palatinate, known for its strategic location at the confluence of the Rhine and Moselle rivers and its well-preserved fortresses and old town.
-
E.
Duisburg
Duisburg is a major industrial and port city in western Germany’s Ruhr region, known for its steel production and one of the world’s largest inland harbors.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada66da23c81908f063b44b48b1e53 |
completed | March 8, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e81e6f98819099317f97f0c7f546 |
completed | March 12, 2026, 4:21 p.m. |
Created at: March 8, 2026, 3:06 p.m.