Triple
T20644873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gmunden District |
E507327
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
St. Konrad
St. Konrad is a small Austrian municipality in the state of Upper Austria, known for its rural setting amid the scenic landscapes of the Salzkammergut region.
|
E1442533
|
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: St. Konrad | Statement: [Gmunden District, containsMunicipality, St. Konrad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. Konrad Context triple: [Gmunden District, containsMunicipality, St. Konrad]
-
A.
Konrad
Konrad is a masculine given name of German origin, historically borne by several notable figures including statesmen, nobles, and religious leaders.
-
B.
St. Lorenz
St. Lorenz is a small municipality in the Vöcklabruck District of Upper Austria, known for its scenic lakeside and alpine surroundings.
-
C.
Sankt Heinrich
Sankt Heinrich is a small village in Bavaria, Germany, that forms part of the municipality of Münsing near Lake Starnberg.
-
D.
St. Kajetan
St. Kajetan is the common name for the Theatinerkirche, a prominent Baroque Catholic church in Munich, Germany.
-
E.
Dannhauser
Dannhauser is a small town and local municipality in KwaZulu-Natal, South Africa, known historically for coal mining and agriculture.
- 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: St. Konrad Triple: [Gmunden District, containsMunicipality, St. Konrad]
Generated description
St. Konrad is a small Austrian municipality in the state of Upper Austria, known for its rural setting amid the scenic landscapes of the Salzkammergut region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: St. Konrad Target entity description: St. Konrad is a small Austrian municipality in the state of Upper Austria, known for its rural setting amid the scenic landscapes of the Salzkammergut region.
-
A.
Konrad
Konrad is a masculine given name of German origin, historically borne by several notable figures including statesmen, nobles, and religious leaders.
-
B.
St. Lorenz
St. Lorenz is a small municipality in the Vöcklabruck District of Upper Austria, known for its scenic lakeside and alpine surroundings.
-
C.
Sankt Heinrich
Sankt Heinrich is a small village in Bavaria, Germany, that forms part of the municipality of Münsing near Lake Starnberg.
-
D.
St. Kajetan
St. Kajetan is the common name for the Theatinerkirche, a prominent Baroque Catholic church in Munich, Germany.
-
E.
Dannhauser
Dannhauser is a small town and local municipality in KwaZulu-Natal, South Africa, known historically for coal mining and agriculture.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1dd79481909de985d03ab861c2 |
completed | April 20, 2026, 10:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08c58e9b0081908fd2c4f3d8022401 |
completed | May 16, 2026, 7:29 p.m. |
| NEDg | Description generation | batch_6a08c65993408190859c75fb65ade257 |
completed | May 16, 2026, 7:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08c78fe4d48190a7a69f65f64ac66c |
completed | May 16, 2026, 7:37 p.m. |
Created at: April 16, 2026, 11:43 a.m.