Triple
T19489699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pfäffikersee |
E487614
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Hittnau
Hittnau is a municipality in the canton of Zurich in Switzerland, known for its rural character and proximity to lakes and rolling countryside.
|
E1394654
|
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: Hittnau | Statement: [Pfäffikersee, locatedIn, Hittnau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hittnau Context triple: [Pfäffikersee, locatedIn, Hittnau]
-
A.
Hundwil
Hundwil is a small Swiss municipality known for its rural character and traditional Appenzell culture in northeastern Switzerland.
-
B.
Kesswil
Kesswil is a small Swiss village on the shores of Lake Constance, best known as the birthplace of the influential psychiatrist and psychoanalyst Carl Gustav Jung.
-
C.
Leutwil
Leutwil is a small municipality in the canton of Aargau in northern Switzerland, known for its rural character and scenic surroundings.
-
D.
Bäriswil
Bäriswil is a small municipality in the canton of Bern in Switzerland, known for its rural character and proximity to the city of Bern.
-
E.
Hergiswil
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
- 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: Hittnau Triple: [Pfäffikersee, locatedIn, Hittnau]
Generated description
Hittnau is a municipality in the canton of Zurich in Switzerland, known for its rural character and proximity to lakes and rolling countryside.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hittnau Target entity description: Hittnau is a municipality in the canton of Zurich in Switzerland, known for its rural character and proximity to lakes and rolling countryside.
-
A.
Hundwil
Hundwil is a small Swiss municipality known for its rural character and traditional Appenzell culture in northeastern Switzerland.
-
B.
Kesswil
Kesswil is a small Swiss village on the shores of Lake Constance, best known as the birthplace of the influential psychiatrist and psychoanalyst Carl Gustav Jung.
-
C.
Leutwil
Leutwil is a small municipality in the canton of Aargau in northern Switzerland, known for its rural character and scenic surroundings.
-
D.
Bäriswil
Bäriswil is a small municipality in the canton of Bern in Switzerland, known for its rural character and proximity to the city of Bern.
-
E.
Hergiswil
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6348ad4088190b530f47efca90165 |
completed | April 20, 2026, 2:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07bd4c2de48190843b04b1a1eeaa8f |
completed | May 16, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_6a07bde28e848190aaa9c4a06b31bdb6 |
completed | May 16, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07bed4c8d8819094fafce7eee69ee7 |
completed | May 16, 2026, 12:48 a.m. |
Created at: April 10, 2026, 1:39 p.m.