Triple
T4938361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaduz |
E110866
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Triesen
Triesen is a municipality in the southern part of Liechtenstein, known for its historic village center and scenic Alpine surroundings.
|
E491902
|
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: Triesen | Statement: [Vaduz, borderedBy, Triesen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Triesen Context triple: [Vaduz, borderedBy, Triesen]
-
A.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
B.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
C.
Straubing
Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
-
D.
Vienenburg
Vienenburg is a district of Goslar in Lower Saxony, Germany, known for its historic town center and proximity to the Harz Mountains.
-
E.
Passau
Passau is a historic city in southeastern Germany, renowned for its picturesque old town and location at the meeting point of three rivers: the Danube, Inn, and Ilz.
- 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: Triesen Triple: [Vaduz, borderedBy, Triesen]
Generated description
Triesen is a municipality in the southern part of Liechtenstein, known for its historic village center and scenic Alpine surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Triesen Target entity description: Triesen is a municipality in the southern part of Liechtenstein, known for its historic village center and scenic Alpine surroundings.
-
A.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
B.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
C.
Straubing
Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
-
D.
Vienenburg
Vienenburg is a district of Goslar in Lower Saxony, Germany, known for its historic town center and proximity to the Harz Mountains.
-
E.
Passau
Passau is a historic city in southeastern Germany, renowned for its picturesque old town and location at the meeting point of three rivers: the Danube, Inn, and Ilz.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7088f6e48190bf09e58ab053a4d1 |
completed | March 20, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0daa53481908c705ca3698ab777 |
completed | March 21, 2026, 2:53 p.m. |
| NEDg | Description generation | batch_69beb16170408190a04dded7fcc512d8 |
completed | March 21, 2026, 2:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69beb1c3bc5c8190b8a58baf2cd1ad44 |
completed | March 21, 2026, 2:57 p.m. |
Created at: March 20, 2026, 1:31 p.m.