Triple
T6869119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flachgau |
E158492
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Grabensee
Grabensee is a small lake in the Austrian state of Salzburg, known for its natural surroundings and recreational opportunities.
|
E625339
|
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: Grabensee | Statement: [Flachgau, contains, Grabensee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grabensee Context triple: [Flachgau, contains, Grabensee]
-
A.
Hallwilersee
Hallwilersee is a scenic lake in the Swiss cantons of Aargau and Lucerne, popular for recreation, boating, and nature conservation.
-
B.
Alpsee
Alpsee is a picturesque alpine lake in Bavaria, Germany, renowned for its clear waters and scenic setting near the royal castles of Neuschwanstein and Hohenschwangau.
-
C.
Staffelsee
Staffelsee is a picturesque lake in southern Bavaria, Germany, known for its islands, warm bathing waters, and scenic Alpine surroundings.
-
D.
Schlosssee
Schlosssee is a scenic lake in the spa town of Bad Waldsee in southern Germany, known for recreation and its picturesque natural setting.
-
E.
Hintersee
Hintersee is a small Austrian municipality in the state of Salzburg, known for its scenic alpine landscapes and nearby mountain lake.
- 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: Grabensee Triple: [Flachgau, contains, Grabensee]
Generated description
Grabensee is a small lake in the Austrian state of Salzburg, known for its natural surroundings and recreational opportunities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grabensee Target entity description: Grabensee is a small lake in the Austrian state of Salzburg, known for its natural surroundings and recreational opportunities.
-
A.
Hallwilersee
Hallwilersee is a scenic lake in the Swiss cantons of Aargau and Lucerne, popular for recreation, boating, and nature conservation.
-
B.
Alpsee
Alpsee is a picturesque alpine lake in Bavaria, Germany, renowned for its clear waters and scenic setting near the royal castles of Neuschwanstein and Hohenschwangau.
-
C.
Staffelsee
Staffelsee is a picturesque lake in southern Bavaria, Germany, known for its islands, warm bathing waters, and scenic Alpine surroundings.
-
D.
Schlosssee
Schlosssee is a scenic lake in the spa town of Bad Waldsee in southern Germany, known for recreation and its picturesque natural setting.
-
E.
Hintersee
Hintersee is a small Austrian municipality in the state of Salzburg, known for its scenic alpine landscapes and nearby mountain lake.
- 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_69c68831e3648190a643c328122e4d43 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8a916a88190b81551731dff2898 |
completed | March 27, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c74299ae148190a56c7b1ee8829f40 |
completed | March 28, 2026, 2:53 a.m. |
| NEDg | Description generation | batch_69c743a639f88190a0758194433322bf |
completed | March 28, 2026, 2:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7445fbd488190938ec3dd59cbeb2c |
completed | March 28, 2026, 3 a.m. |
Created at: March 27, 2026, 2:22 p.m.