Triple
T9495219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagria |
E228986
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Sierksdorf
Sierksdorf is a small coastal municipality in northern Germany, known for its Baltic Sea beaches and the Hansa-Park amusement park.
|
E881716
|
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: Sierksdorf | Statement: [Wagria, contains, Sierksdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sierksdorf Context triple: [Wagria, contains, Sierksdorf]
-
A.
Suhrendorf
Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
-
B.
Siegsdorf
Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
-
C.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
-
D.
Nordendorf
Nordendorf is a small municipality in Bavaria, Germany, situated within the Augsburg district.
-
E.
Heinersdorf
Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
- 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: Sierksdorf Triple: [Wagria, contains, Sierksdorf]
Generated description
Sierksdorf is a small coastal municipality in northern Germany, known for its Baltic Sea beaches and the Hansa-Park amusement park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sierksdorf Target entity description: Sierksdorf is a small coastal municipality in northern Germany, known for its Baltic Sea beaches and the Hansa-Park amusement park.
-
A.
Suhrendorf
Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
-
B.
Siegsdorf
Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
-
C.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
-
D.
Nordendorf
Nordendorf is a small municipality in Bavaria, Germany, situated within the Augsburg district.
-
E.
Heinersdorf
Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95eb87b081908fc7255598cd9a24 |
completed | April 1, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbb6bb34548190aac9d2af05477750 |
completed | April 12, 2026, 3:14 p.m. |
| NEDg | Description generation | batch_69dbbb8b0e5c8190afa9aaa134bcebf2 |
completed | April 12, 2026, 3:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dbbc3ce1008190a16d442a22d45967 |
completed | April 12, 2026, 3:37 p.m. |
Created at: March 30, 2026, 7:56 p.m.