Triple
T7915917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Nidwalden |
E183826
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Hergiswil
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
|
E724903
|
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: Hergiswil | Statement: [canton of Nidwalden, hasMunicipality, Hergiswil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hergiswil Context triple: [canton of Nidwalden, hasMunicipality, Hergiswil]
-
A.
Walchwil
Walchwil is a picturesque Swiss municipality in the canton of Zug, known for its scenic location on the eastern shore of Lake Zug and views of the surrounding Alps.
-
B.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
C.
Richterswil
Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
-
D.
Wädenswil
Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
-
E.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
- 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: Hergiswil Triple: [canton of Nidwalden, hasMunicipality, Hergiswil]
Generated description
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hergiswil Target entity description: Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
-
A.
Walchwil
Walchwil is a picturesque Swiss municipality in the canton of Zug, known for its scenic location on the eastern shore of Lake Zug and views of the surrounding Alps.
-
B.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
C.
Richterswil
Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
-
D.
Wädenswil
Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
-
E.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
- 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_69ca828efbe48190bd48482650182e79 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a76ae688190b068e4c92603a16d |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd943f5aec8190a42d3932ef7c54fd |
completed | April 1, 2026, 9:55 p.m. |
| NEDg | Description generation | batch_69cda62070888190b55b3f54d29e28e7 |
completed | April 1, 2026, 11:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdb21a65d88190a19dd41f95d173c8 |
completed | April 2, 2026, 12:02 a.m. |
Created at: March 30, 2026, 5:05 p.m.