Triple
T12709097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasli-Aare basin |
E303667
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Hasliberg
Hasliberg is a Swiss alpine village and municipality in the canton of Bern, known for its mountain scenery and ski and hiking resort facilities.
|
E999622
|
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: Hasliberg | Statement: [Hasli-Aare basin, contains, Hasliberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasliberg Context triple: [Hasli-Aare basin, contains, Hasliberg]
-
A.
Hornberg
Hornberg is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its scenic landscape and traditional cuckoo clock craftsmanship.
-
B.
Hallbergmoos
Hallbergmoos is a municipality in Bavaria, Germany, known for hosting major aerospace and technology companies near Munich.
-
C.
Halderberge
Halderberge is a municipality in the Dutch province of North Brabant, known for its historic towns such as Oudenbosch and its mix of rural landscapes and small urban centers.
-
D.
Landensberg
Landensberg is a small municipality in the Bavarian region of southern Germany.
-
E.
Machtolsheim
Machtolsheim is a village in the Alb-Donau district of Baden-Württemberg, Germany, that forms part of the town of Laichingen.
- 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: Hasliberg Triple: [Hasli-Aare basin, contains, Hasliberg]
Generated description
Hasliberg is a Swiss alpine village and municipality in the canton of Bern, known for its mountain scenery and ski and hiking resort facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hasliberg Target entity description: Hasliberg is a Swiss alpine village and municipality in the canton of Bern, known for its mountain scenery and ski and hiking resort facilities.
-
A.
Hornberg
Hornberg is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its scenic landscape and traditional cuckoo clock craftsmanship.
-
B.
Hallbergmoos
Hallbergmoos is a municipality in Bavaria, Germany, known for hosting major aerospace and technology companies near Munich.
-
C.
Halderberge
Halderberge is a municipality in the Dutch province of North Brabant, known for its historic towns such as Oudenbosch and its mix of rural landscapes and small urban centers.
-
D.
Landensberg
Landensberg is a small municipality in the Bavarian region of southern Germany.
-
E.
Machtolsheim
Machtolsheim is a village in the Alb-Donau district of Baden-Württemberg, Germany, that forms part of the town of Laichingen.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96207b2d881908314efc3e350aa78 |
completed | April 10, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c7e0a44819093c90f593ad616b9 |
completed | May 2, 2026, 10:36 p.m. |
| NEDg | Description generation | batch_69f67d64ed3481908d434c20796866f9 |
completed | May 2, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67e82e35081909c4b5fad7e941610 |
completed | May 2, 2026, 10:45 p.m. |
Created at: April 9, 2026, 5:23 p.m.