Triple
T11170878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eggersriet |
E264269
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object |
Untereggen
Untereggen is a small Swiss municipality in the canton of St. Gallen, known for its rural character and location in the country’s northeastern region.
|
E919672
|
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: Untereggen | Statement: [Eggersriet, hasNeighboringMunicipality, Untereggen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Untereggen Context triple: [Eggersriet, hasNeighboringMunicipality, Untereggen]
-
A.
Waltershof
Waltershof is an industrial and port district of Hamburg, Germany, located within the borough of Hamburg-Mitte.
-
B.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
C.
Besseggen
Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
-
D.
Bettlach
Bettlach is a Swiss municipality located in the canton of Solothurn.
-
E.
Lichtensteig
Lichtensteig is a small historic town in the canton of St. Gallen in northeastern Switzerland, known for its well-preserved old town and picturesque setting in the Toggenburg region.
- 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: Untereggen Triple: [Eggersriet, hasNeighboringMunicipality, Untereggen]
Generated description
Untereggen is a small Swiss municipality in the canton of St. Gallen, known for its rural character and location in the country’s northeastern region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Untereggen Target entity description: Untereggen is a small Swiss municipality in the canton of St. Gallen, known for its rural character and location in the country’s northeastern region.
-
A.
Waltershof
Waltershof is an industrial and port district of Hamburg, Germany, located within the borough of Hamburg-Mitte.
-
B.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
C.
Besseggen
Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
-
D.
Bettlach
Bettlach is a Swiss municipality located in the canton of Solothurn.
-
E.
Lichtensteig
Lichtensteig is a small historic town in the canton of St. Gallen in northeastern Switzerland, known for its well-preserved old town and picturesque setting in the Toggenburg region.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e89660208190b1d9e91529f5d246 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5427918f08190ac1fdf3e0aff036f |
completed | April 19, 2026, 9 p.m. |
| NEDg | Description generation | batch_69e5474879088190990468d960b26739 |
completed | April 19, 2026, 9:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e54eccdd3881908536ee3f9f4ef516 |
completed | April 19, 2026, 9:53 p.m. |
Created at: April 8, 2026, 9:29 p.m.