Triple
T7407312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludwigshafen am Rhein |
E170906
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Friesenheim
Friesenheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
|
E666516
|
NE FINISHED |
How this triple was built (4 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: Friesenheim | Statement: [Ludwigshafen am Rhein, hasDistrict, Friesenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Friesenheim Context triple: [Ludwigshafen am Rhein, hasDistrict, Friesenheim]
-
A.
Friesenheim
Friesenheim is a municipality in the Ortenau district of the state of Baden-Württemberg in southwestern Germany.
-
B.
Fritzlar
Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
-
C.
Freiolsheim
Freiolsheim is a village and district of the town of Gaggenau in the Rastatt district of Baden-Württemberg, Germany.
-
D.
Langenau
Langenau is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its historic center and proximity to the Swabian Jura.
-
E.
Bruchsal
Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Friesenheim Triple: [Ludwigshafen am Rhein, hasDistrict, Friesenheim]
Generated description
Friesenheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Friesenheim Target entity description: Friesenheim is a district of the industrial city of Ludwigshafen am Rhein in the German state of Rhineland-Palatinate.
-
A.
Friesenheim
Friesenheim is a municipality in the Ortenau district of the state of Baden-Württemberg in southwestern Germany.
-
B.
Fritzlar
Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
-
C.
Freiolsheim
Freiolsheim is a village and district of the town of Gaggenau in the Rastatt district of Baden-Württemberg, Germany.
-
D.
Langenau
Langenau is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its historic center and proximity to the Swabian Jura.
-
E.
Bruchsal
Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
- F. None of above. chosen
Provenance (5 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f298f2388190afc944c9bc78749a |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83440200081909cf0c747697d644a |
completed | March 28, 2026, 8:04 p.m. |
| NEDg | Description generation | batch_69c834ecb15081909acc684fcc8969aa |
completed | March 28, 2026, 8:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c835d2474081908ec1e93c1ced0b1f |
completed | March 28, 2026, 8:10 p.m. |
Created at: March 27, 2026, 3:10 p.m.