Triple
T6196262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oensingen |
E138514
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object |
Langenbruck
Langenbruck is a small Swiss municipality in the canton of Basel-Landschaft, known for its scenic Jura landscape and rural character.
|
E575481
|
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: Langenbruck | Statement: [Oensingen, neighboringMunicipality, Langenbruck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langenbruck Context triple: [Oensingen, neighboringMunicipality, Langenbruck]
-
A.
Langensalza
Langensalza is a historic town in Thuringia, central Germany, known for its spa facilities and as the site of several notable battles.
-
B.
Mülbracht
Mülbracht is a historical locality in the Holy Roman Empire known primarily as the birthplace of the Dutch Golden Age engraver and painter Hendrick Goltzius.
-
C.
Köstendorf
Köstendorf is a small Austrian municipality in the state of Salzburg, known for its rural character and proximity to the city of Salzburg.
-
D.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
-
E.
Königstein
Königstein is a small historic town in Saxon Switzerland, eastern Germany, best known for the imposing Königstein Fortress overlooking the Elbe River.
- 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: Langenbruck Triple: [Oensingen, neighboringMunicipality, Langenbruck]
Generated description
Langenbruck is a small Swiss municipality in the canton of Basel-Landschaft, known for its scenic Jura landscape and rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Langenbruck Target entity description: Langenbruck is a small Swiss municipality in the canton of Basel-Landschaft, known for its scenic Jura landscape and rural character.
-
A.
Langensalza
Langensalza is a historic town in Thuringia, central Germany, known for its spa facilities and as the site of several notable battles.
-
B.
Mülbracht
Mülbracht is a historical locality in the Holy Roman Empire known primarily as the birthplace of the Dutch Golden Age engraver and painter Hendrick Goltzius.
-
C.
Köstendorf
Köstendorf is a small Austrian municipality in the state of Salzburg, known for its rural character and proximity to the city of Salzburg.
-
D.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
-
E.
Königstein
Königstein is a small historic town in Saxon Switzerland, eastern Germany, best known for the imposing Königstein Fortress overlooking the Elbe River.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0624571508190bd273b4a051fbe41 |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f234ffc8190a6e8166e2ac554a8 |
completed | March 23, 2026, 4:49 p.m. |
| NEDg | Description generation | batch_69c1e32429f48190bc18f4d78f3c79e8 |
completed | March 24, 2026, 1:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1e4844f848190bf67d916851514bc |
completed | March 24, 2026, 1:10 a.m. |
Created at: March 22, 2026, 4:20 p.m.