Triple
T18072257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Königswinter |
E432458
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Stadtteil Altstadt
Stadtteil Altstadt is the historic old town district of Königswinter, known for its traditional architecture and central location along the Rhine.
|
E1303635
|
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: Stadtteil Altstadt | Statement: [Königswinter, hasPart, Stadtteil Altstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stadtteil Altstadt Context triple: [Königswinter, hasPart, Stadtteil Altstadt]
-
A.
Stadtmitte
Stadtmitte is the central urban district of the town of Bad Honnef in North Rhine-Westphalia, Germany.
-
B.
Stadtmitte
Stadtmitte is the central urban district and main downtown area of the town of Eberswalde in Germany.
-
C.
Stadtmitte
Stadtmitte is a central Berlin U-Bahn station serving as an important interchange and access point to the city’s historic Mitte district.
-
D.
Stadtbezirk Innenstadt
Stadtbezirk Innenstadt is a central urban district of Frankfurt am Main, Germany, encompassing key inner-city neighborhoods and major commercial and cultural areas.
-
E.
Altstadt-Lehel borough
Altstadt-Lehel is a central Munich borough that encompasses the historic Old Town and some of the city’s most prominent cultural and architectural landmarks.
- 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: Stadtteil Altstadt Triple: [Königswinter, hasPart, Stadtteil Altstadt]
Generated description
Stadtteil Altstadt is the historic old town district of Königswinter, known for its traditional architecture and central location along the Rhine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stadtteil Altstadt Target entity description: Stadtteil Altstadt is the historic old town district of Königswinter, known for its traditional architecture and central location along the Rhine.
-
A.
Stadtmitte
Stadtmitte is the central urban district and main downtown area of the town of Eberswalde in Germany.
-
B.
Stadtmitte
Stadtmitte is a central Berlin U-Bahn station serving as an important interchange and access point to the city’s historic Mitte district.
-
C.
Stadtmitte
Stadtmitte is the central urban district of the town of Bad Honnef in North Rhine-Westphalia, Germany.
-
D.
Stadtbezirk Innenstadt
Stadtbezirk Innenstadt is a central urban district of Frankfurt am Main, Germany, encompassing key inner-city neighborhoods and major commercial and cultural areas.
-
E.
Altstadt-Lehel borough
Altstadt-Lehel is a central Munich borough that encompasses the historic Old Town and some of the city’s most prominent cultural and architectural landmarks.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ccef022c81909be41b2c3a3ee68e |
completed | April 19, 2026, 12:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03567685fc8190a63da27de99a1101 |
completed | May 12, 2026, 4:33 p.m. |
| NEDg | Description generation | batch_6a0357dd52dc8190990b5dc2fe1b4720 |
completed | May 12, 2026, 4:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03585051d4819085e4ea76b0a8ea8b |
completed | May 12, 2026, 4:41 p.m. |
Created at: April 10, 2026, 10:26 a.m.