Triple
T9975248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiserslautern Hauptbahnhof |
E196309
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object |
Kusel
Kusel is a small town in the German state of Rhineland-Palatinate, known as the administrative center of the Kusel district in the Western Palatinate region.
|
E839122
|
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: Kusel | Statement: [Kaiserslautern Hauptbahnhof, connectsTo, Kusel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kusel Context triple: [Kaiserslautern Hauptbahnhof, connectsTo, Kusel]
-
A.
Schwarzenbach
Schwarzenbach is a small river in Switzerland that serves as a tributary of the Murg.
-
B.
Vaterstetten
Vaterstetten is a municipality in the district of Ebersberg near Munich in Bavaria, Germany, known as a residential suburb with strong transport links to the Bavarian capital.
-
C.
Kreuth
Kreuth is a Bavarian municipality in southern Germany, known for its alpine landscape and location near Lake Tegernsee in the Bavarian Alps.
-
D.
Siegbach
Siegbach is a small rural municipality in the German state of Hesse, known for its scenic location within the wooded hills of central Germany.
-
E.
Schiltach
Schiltach is a small historic town in Germany’s Black Forest region, known for its well-preserved half-timbered houses and picturesque riverside setting.
- 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: Kusel Triple: [Kaiserslautern Hauptbahnhof, connectsTo, Kusel]
Generated description
Kusel is a small town in the German state of Rhineland-Palatinate, known as the administrative center of the Kusel district in the Western Palatinate region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kusel Target entity description: Kusel is a small town in the German state of Rhineland-Palatinate, known as the administrative center of the Kusel district in the Western Palatinate region.
-
A.
Schwarzenbach
Schwarzenbach is a small river in Switzerland that serves as a tributary of the Murg.
-
B.
Vaterstetten
Vaterstetten is a municipality in the district of Ebersberg near Munich in Bavaria, Germany, known as a residential suburb with strong transport links to the Bavarian capital.
-
C.
Kreuth
Kreuth is a Bavarian municipality in southern Germany, known for its alpine landscape and location near Lake Tegernsee in the Bavarian Alps.
-
D.
Siegbach
Siegbach is a small rural municipality in the German state of Hesse, known for its scenic location within the wooded hills of central Germany.
-
E.
Schiltach
Schiltach is a small historic town in Germany’s Black Forest region, known for its well-preserved half-timbered houses and picturesque riverside setting.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb84b47308190aa2f94fa7320cdc3 |
completed | April 2, 2026, 12:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d299e3d5fc8190a953be3ebd8250e6 |
completed | April 5, 2026, 5:20 p.m. |
| NEDg | Description generation | batch_69d29b985e308190a6ec3966e02f429c |
completed | April 5, 2026, 5:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d29c5f64c881909aa3d093422fe475 |
completed | April 5, 2026, 5:31 p.m. |
Created at: March 30, 2026, 8:48 p.m.