Triple
T9413968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Rosenheim |
E226767
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Simssee
Simssee is a natural lake in Upper Bavaria, Germany, known for its scenic surroundings and recreational opportunities near the city of Rosenheim.
|
E797517
|
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: Simssee | Statement: [district of Rosenheim, contains, Simssee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simssee Context triple: [district of Rosenheim, contains, Simssee]
-
A.
Schweinheim
Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
-
B.
Meimsheim
Meimsheim is a village in the municipality of Brackenheim in the Heilbronn district of Baden-Württemberg, Germany.
-
C.
Seewiesen
Seewiesen is a research locality in Bavaria, Germany, best known for its ornithological and behavioral science institutes associated with Konrad Lorenz and other pioneering ethologists.
-
D.
Johannisberg
Johannisberg is a prominent peak in the Austrian Alps, located in the High Tauern range near the Grossglockner.
-
E.
Weilerswist
Weilerswist is a municipality in the Rhein-Erft district of North Rhine-Westphalia, Germany, known for its rural character and proximity to the cities of Cologne and Bonn.
- 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: Simssee Triple: [district of Rosenheim, contains, Simssee]
Generated description
Simssee is a natural lake in Upper Bavaria, Germany, known for its scenic surroundings and recreational opportunities near the city of Rosenheim.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Simssee Target entity description: Simssee is a natural lake in Upper Bavaria, Germany, known for its scenic surroundings and recreational opportunities near the city of Rosenheim.
-
A.
Schweinheim
Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
-
B.
Meimsheim
Meimsheim is a village in the municipality of Brackenheim in the Heilbronn district of Baden-Württemberg, Germany.
-
C.
Seewiesen
Seewiesen is a research locality in Bavaria, Germany, best known for its ornithological and behavioral science institutes associated with Konrad Lorenz and other pioneering ethologists.
-
D.
Johannisberg
Johannisberg is a prominent peak in the Austrian Alps, located in the High Tauern range near the Grossglockner.
-
E.
Weilerswist
Weilerswist is a municipality in the Rhein-Erft district of North Rhine-Westphalia, Germany, known for its rural character and proximity to the cities of Cologne and Bonn.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c680e48190be82e3829e8711f0 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107b63cf48190a072e3434a7b85a8 |
completed | April 4, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_69d108466fb481909682fcaac354b312 |
completed | April 4, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d108be82888190b0ec08119cd00b68 |
completed | April 4, 2026, 12:49 p.m. |
Created at: March 30, 2026, 7:47 p.m.