Triple
T12055625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Churfirsten |
E287033
|
entity |
| Predicate | nearestTown |
P350
|
FINISHED |
| Object |
Unterterzen
Unterterzen is a small Swiss village on the shores of Lake Walen in the canton of St. Gallen, known as a gateway to the nearby Churfirsten mountain range and the Flumserberg ski area.
|
E960892
|
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: Unterterzen | Statement: [Churfirsten, nearestTown, Unterterzen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unterterzen Context triple: [Churfirsten, nearestTown, Unterterzen]
-
A.
Unterägeri
Unterägeri is a Swiss municipality in the canton of Zug, known for its scenic location by Lake Ägeri and surrounding pre-Alpine landscapes.
-
B.
Pottenstein
Pottenstein is a small town in Lower Austria known for its scenic surroundings and traditional Austrian character.
-
C.
Blatzheim
Blatzheim is a village and district within the town of Kerpen in North Rhine-Westphalia, Germany.
-
D.
Oberthulba
Oberthulba is a small municipality in northern Bavaria, Germany, known for its rural character and location within the Franconian Saale region.
-
E.
Stutterheim
Stutterheim is a small town in South Africa’s Eastern Cape province, known for its forestry, agriculture, and scenic setting near the Amathole Mountains.
- 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: Unterterzen Triple: [Churfirsten, nearestTown, Unterterzen]
Generated description
Unterterzen is a small Swiss village on the shores of Lake Walen in the canton of St. Gallen, known as a gateway to the nearby Churfirsten mountain range and the Flumserberg ski area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Unterterzen Target entity description: Unterterzen is a small Swiss village on the shores of Lake Walen in the canton of St. Gallen, known as a gateway to the nearby Churfirsten mountain range and the Flumserberg ski area.
-
A.
Unterägeri
Unterägeri is a Swiss municipality in the canton of Zug, known for its scenic location by Lake Ägeri and surrounding pre-Alpine landscapes.
-
B.
Pottenstein
Pottenstein is a small town in Lower Austria known for its scenic surroundings and traditional Austrian character.
-
C.
Blatzheim
Blatzheim is a village and district within the town of Kerpen in North Rhine-Westphalia, Germany.
-
D.
Oberthulba
Oberthulba is a small municipality in northern Bavaria, Germany, known for its rural character and location within the Franconian Saale region.
-
E.
Stutterheim
Stutterheim is a small town in South Africa’s Eastern Cape province, known for its forestry, agriculture, and scenic setting near the Amathole Mountains.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90425258c8190ba7b3b837c439253 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49dea043c8190a74ffb448bbae5d0 |
completed | May 1, 2026, 12:34 p.m. |
| NEDg | Description generation | batch_69f53d96c3f08190847ba49929b7628f |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f56505c0b481909f9caaf338f73033 |
completed | May 2, 2026, 2:44 a.m. |
Created at: April 8, 2026, 9:47 p.m.