Triple
T18108275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Spittal an der Drau |
E433404
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Seeboden
Seeboden is a lakeside market town and popular tourist resort on the shore of Lake Millstatt in Carinthia, Austria.
|
E1306453
|
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: Seeboden | Statement: [district of Spittal an der Drau, containsMunicipality, Seeboden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seeboden Context triple: [district of Spittal an der Drau, containsMunicipality, Seeboden]
-
A.
Blausee
Blausee is a small, crystal-clear alpine lake in the Swiss Bernese Oberland, famed for its striking blue waters and tranquil forest surroundings.
-
B.
Unterer See
Unterer See is a small lake located in the town of Böblingen in the German state of Baden-Württemberg.
-
C.
Totes Meer
Totes Meer is a surreal 1940–41 wartime painting by British artist Paul Nash depicting a sea of wrecked German aircraft under a moonlit sky.
-
D.
Obersee
Obersee is a small, picturesque alpine lake in Bavaria, Germany, known for its clear emerald waters and dramatic mountain surroundings near the Königssee.
-
E.
Seevetal
Seevetal is a large municipality in Lower Saxony, Germany, located just south of Hamburg and known for its suburban character and good transport connections.
- 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: Seeboden Triple: [district of Spittal an der Drau, containsMunicipality, Seeboden]
Generated description
Seeboden is a lakeside market town and popular tourist resort on the shore of Lake Millstatt in Carinthia, Austria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seeboden Target entity description: Seeboden is a lakeside market town and popular tourist resort on the shore of Lake Millstatt in Carinthia, Austria.
-
A.
Blausee
Blausee is a small, crystal-clear alpine lake in the Swiss Bernese Oberland, famed for its striking blue waters and tranquil forest surroundings.
-
B.
Unterer See
Unterer See is a small lake located in the town of Böblingen in the German state of Baden-Württemberg.
-
C.
Totes Meer
Totes Meer is a surreal 1940–41 wartime painting by British artist Paul Nash depicting a sea of wrecked German aircraft under a moonlit sky.
-
D.
Obersee
Obersee is a small, picturesque alpine lake in Bavaria, Germany, known for its clear emerald waters and dramatic mountain surroundings near the Königssee.
-
E.
Seevetal
Seevetal is a large municipality in Lower Saxony, Germany, located just south of Hamburg and known for its suburban character and good transport connections.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddbbfae88190aa77f498dbb9edcb |
completed | April 19, 2026, 1:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a037c36eea4819089619fd895c05893 |
completed | May 12, 2026, 7:15 p.m. |
| NEDg | Description generation | batch_6a037e2086708190af48c53800a729fd |
completed | May 12, 2026, 7:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a037eba5fb88190b2c131260f28df84 |
completed | May 12, 2026, 7:25 p.m. |
Created at: April 10, 2026, 10:28 a.m.