Triple
T11231830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlottenburg-Wilmersdorf |
E265840
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Westend
Westend is a residential and commercial locality in Berlin known for its affluent neighborhoods, green spaces, and proximity to the Olympic Stadium.
|
E912960
|
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: Westend | Statement: [Charlottenburg-Wilmersdorf, contains, Westend]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Westend Context triple: [Charlottenburg-Wilmersdorf, contains, Westend]
-
A.
Westend
Westend is a prominent and affluent district in Frankfurt am Main, Germany, known for its elegant residential areas and concentration of banks and corporate offices.
-
B.
Soho
Soho is a vibrant central London district famed for its nightlife, entertainment venues, and diverse cultural scene.
-
C.
Soho
Soho is an inner-city district of Birmingham, England, historically known for its industrial heritage and diverse local community.
-
D.
West End
West End is an upscale neighborhood in northwest Washington, D.C., known for its luxury hotels, condominiums, and proximity to Georgetown and Dupont Circle.
-
E.
West End
West End is London’s renowned theatre district, famous for its high-profile stage productions and vibrant entertainment scene.
- 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: Westend Triple: [Charlottenburg-Wilmersdorf, contains, Westend]
Generated description
Westend is a residential and commercial locality in Berlin known for its affluent neighborhoods, green spaces, and proximity to the Olympic Stadium.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Westend Target entity description: Westend is a residential and commercial locality in Berlin known for its affluent neighborhoods, green spaces, and proximity to the Olympic Stadium.
-
A.
Westend
Westend is a prominent and affluent district in Frankfurt am Main, Germany, known for its elegant residential areas and concentration of banks and corporate offices.
-
B.
Soho
Soho is a vibrant central London district famed for its nightlife, entertainment venues, and diverse cultural scene.
-
C.
Soho
Soho is an inner-city district of Birmingham, England, historically known for its industrial heritage and diverse local community.
-
D.
West End
West End is an upscale neighborhood in northwest Washington, D.C., known for its luxury hotels, condominiums, and proximity to Georgetown and Dupont Circle.
-
E.
West End
West End is London’s renowned theatre district, famous for its high-profile stage productions and vibrant entertainment scene.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9026e1c81909456ac946bbba972 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad49b5cc8190b99cb2cd8de72109 |
completed | April 19, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69e4b12dd658819085c25d3edac2d66c |
completed | April 19, 2026, 10:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4b3d23b18819096f3a11aecc732bd |
completed | April 19, 2026, 10:52 a.m. |
Created at: April 8, 2026, 9:30 p.m.