Triple
T1506029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armgard von Cramm |
E33903
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Bad Driburg
Bad Driburg is a small spa town in North Rhine-Westphalia, Germany, known for its mineral springs and health resorts.
|
E195900
|
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: Bad Driburg | Statement: [Armgard von Cramm, placeOfBirth, Bad Driburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Driburg Context triple: [Armgard von Cramm, placeOfBirth, Bad Driburg]
-
A.
Bad Godesberg
Bad Godesberg is a district in the city of Bonn, Germany, known for its affluent residential areas, former diplomatic missions, and scenic location along the Rhine River.
-
B.
Bad Salzdetfurth
Bad Salzdetfurth is a spa town in Lower Saxony, Germany, known for its historic saltworks and therapeutic health resorts.
-
C.
Wuppertal
Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
-
D.
Ingolstadt
Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
-
E.
Bockenheim
Bockenheim is a lively urban district of Frankfurt am Main known for its mix of residential areas, shops, and university facilities.
- 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: Bad Driburg Triple: [Armgard von Cramm, placeOfBirth, Bad Driburg]
Generated description
Bad Driburg is a small spa town in North Rhine-Westphalia, Germany, known for its mineral springs and health resorts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Driburg Target entity description: Bad Driburg is a small spa town in North Rhine-Westphalia, Germany, known for its mineral springs and health resorts.
-
A.
Bad Godesberg
Bad Godesberg is a district in the city of Bonn, Germany, known for its affluent residential areas, former diplomatic missions, and scenic location along the Rhine River.
-
B.
Bad Salzdetfurth
Bad Salzdetfurth is a spa town in Lower Saxony, Germany, known for its historic saltworks and therapeutic health resorts.
-
C.
Wuppertal
Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
-
D.
Ingolstadt
Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
-
E.
Bockenheim
Bockenheim is a lively urban district of Frankfurt am Main known for its mix of residential areas, shops, and university facilities.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a88735f8a8819089177a4d3e4a0211 |
completed | March 4, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0bd0f5c8190b5bfd26995f00a0c |
completed | March 8, 2026, 4:15 p.m. |
| NEDg | Description generation | batch_69ada1a0510481908ed8c36c9ae9a1a0 |
completed | March 8, 2026, 4:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ada26343988190bd067ca97186eb96 |
completed | March 8, 2026, 4:22 p.m. |
Created at: March 4, 2026, 7:24 p.m.