Triple
T20499037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triesenberg |
E503251
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Wangerberg
Wangerberg is a small settlement in the mountainous municipality of Triesenberg in Liechtenstein.
|
E1435604
|
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: Wangerberg | Statement: [Triesenberg, contains, Wangerberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wangerberg Context triple: [Triesenberg, contains, Wangerberg]
-
A.
Belpberg
Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
-
B.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
C.
Wurmberg
Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
-
D.
Wiedensahl
Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
-
E.
Wimberg
Wimberg is a district or neighborhood within the town of Calw in the state of Baden-Württemberg, Germany.
- 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: Wangerberg Triple: [Triesenberg, contains, Wangerberg]
Generated description
Wangerberg is a small settlement in the mountainous municipality of Triesenberg in Liechtenstein.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wangerberg Target entity description: Wangerberg is a small settlement in the mountainous municipality of Triesenberg in Liechtenstein.
-
A.
Belpberg
Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
-
B.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
C.
Wurmberg
Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
-
D.
Wiedensahl
Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
-
E.
Wimberg
Wimberg is a district or neighborhood within the town of Calw in the state of Baden-Württemberg, Germany.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbff210819089900e9a35911f48 |
completed | April 20, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a089d31f68881908b7676ca5561a76f |
completed | May 16, 2026, 4:37 p.m. |
| NEDg | Description generation | batch_6a089db22fcc819094d595a3ce4e19a6 |
completed | May 16, 2026, 4:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a089e4c21d88190a6c1ddf8e0879cb1 |
completed | May 16, 2026, 4:41 p.m. |
Created at: April 16, 2026, 11:35 a.m.