Triple
T10950744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuhlsbüttel |
E258718
|
entity |
| Predicate | hasNeighbouringQuarter |
P96797
|
FINISHED |
| Object |
Hummelsbüttel
Hummelsbüttel is a residential quarter in the borough of Wandsbek in Hamburg, Germany, known for its green spaces and suburban character.
|
E968924
|
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: Hummelsbüttel | Statement: [Fuhlsbüttel, hasNeighbouringQuarter, Hummelsbüttel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hummelsbüttel Context triple: [Fuhlsbüttel, hasNeighbouringQuarter, Hummelsbüttel]
-
A.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
B.
Damsholte
Damsholte is a small village on the Danish island of Møn, known for its rural charm and historic church.
-
C.
Hammelburg
Hammelburg is a historic town in northern Bavaria, Germany, known as one of the country’s oldest wine-growing communities.
-
D.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
E.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
- 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: Hummelsbüttel Triple: [Fuhlsbüttel, hasNeighbouringQuarter, Hummelsbüttel]
Generated description
Hummelsbüttel is a residential quarter in the borough of Wandsbek in Hamburg, Germany, known for its green spaces and suburban character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hummelsbüttel Target entity description: Hummelsbüttel is a residential quarter in the borough of Wandsbek in Hamburg, Germany, known for its green spaces and suburban character.
-
A.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
B.
Damsholte
Damsholte is a small village on the Danish island of Møn, known for its rural charm and historic church.
-
C.
Hammelburg
Hammelburg is a historic town in northern Bavaria, Germany, known as one of the country’s oldest wine-growing communities.
-
D.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
E.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ed2f1c819081ec58457f57889d |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a4d8a3481909c7f8a529d0051c2 |
completed | May 2, 2026, 2:29 p.m. |
| NEDg | Description generation | batch_69f60bda16e48190af8abc0aa8ef41f0 |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60cd1668881908f43d895fcfba0aa |
completed | May 2, 2026, 2:40 p.m. |
Created at: April 8, 2026, 9:23 p.m.