Triple
T14157217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meilen |
E350843
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object |
Uetikon am See
Uetikon am See is a municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland, known for its scenic lakeside setting and residential character.
|
E1083787
|
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: Uetikon am See | Statement: [Meilen, neighboringMunicipality, Uetikon am See]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uetikon am See Context triple: [Meilen, neighboringMunicipality, Uetikon am See]
-
A.
Schönaich
Schönaich is a municipality in the German state of Baden-Württemberg, known for its local community life and international town twinning partnerships.
-
B.
Riehe
Riehe is a small river in Lower Saxony, Germany, known as one of the tributaries feeding into the Innerste.
-
C.
Faulensee
Faulensee is a lakeside village in the Swiss canton of Bern, situated on the southern shore of Lake Thun and known for its scenic Alpine setting.
-
D.
Walperswil
Walperswil is a small municipality in the canton of Bern in Switzerland.
-
E.
Rüthen
Rüthen is a small historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and location in the scenic Sauerland 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: Uetikon am See Triple: [Meilen, neighboringMunicipality, Uetikon am See]
Generated description
Uetikon am See is a municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland, known for its scenic lakeside setting and residential character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Uetikon am See Target entity description: Uetikon am See is a municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland, known for its scenic lakeside setting and residential character.
-
A.
Schönaich
Schönaich is a municipality in the German state of Baden-Württemberg, known for its local community life and international town twinning partnerships.
-
B.
Riehe
Riehe is a small river in Lower Saxony, Germany, known as one of the tributaries feeding into the Innerste.
-
C.
Faulensee
Faulensee is a lakeside village in the Swiss canton of Bern, situated on the southern shore of Lake Thun and known for its scenic Alpine setting.
-
D.
Walperswil
Walperswil is a small municipality in the canton of Bern in Switzerland.
-
E.
Rüthen
Rüthen is a small historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and location in the scenic Sauerland 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61377de48190a3470d28f0edd34a |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7ef4d80819098d210503f5d22e9 |
completed | May 7, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_69fd02cee5e0819086718893d1621481 |
completed | May 7, 2026, 9:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd063668f4819099d52bee7e7cdc32 |
completed | May 7, 2026, 9:37 p.m. |
Created at: April 10, 2026, 12:58 a.m.