Triple
T752302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tegeler See |
E15475
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object |
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
|
E140163
|
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: Hasselwerder | Statement: [Tegeler See, hasIsland, Hasselwerder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasselwerder Context triple: [Tegeler See, hasIsland, Hasselwerder]
-
A.
Bergedorf
Bergedorf is a historic quarter and former independent town in the southeast of Hamburg, Germany, known for its medieval castle and role as a regional administrative and trading center.
-
B.
Seubelsdorf
Seubelsdorf is a village that forms one of the local subdivisions of the town of Lichtenfels in Bavaria, Germany.
-
C.
Hermsdorf
Hermsdorf is a residential locality in the Berlin borough of Reinickendorf, known for its green surroundings and village-like character on the city’s northern edge.
-
D.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
E.
Dessau
Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
- 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: Hasselwerder Triple: [Tegeler See, hasIsland, Hasselwerder]
Generated description
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hasselwerder Target entity description: Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
A.
Bergedorf
Bergedorf is a historic quarter and former independent town in the southeast of Hamburg, Germany, known for its medieval castle and role as a regional administrative and trading center.
-
B.
Seubelsdorf
Seubelsdorf is a village that forms one of the local subdivisions of the town of Lichtenfels in Bavaria, Germany.
-
C.
Hermsdorf
Hermsdorf is a residential locality in the Berlin borough of Reinickendorf, known for its green surroundings and village-like character on the city’s northern edge.
-
D.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
E.
Dessau
Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64d7d2c8190a6059adcb8fbd34f |
completed | March 1, 2026, 8:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac82e8bd788190a20a580bae9bd94e |
completed | March 7, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69ac870e762881909b8fb892a1f0c338 |
completed | March 7, 2026, 8:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac8761ff0481908eeabcc1b10d7492 |
completed | March 7, 2026, 8:15 p.m. |
Created at: March 1, 2026, 7:37 p.m.