Triple
T2616411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katharina von Bora |
E58897
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Lippendorf
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
|
E296801
|
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: Lippendorf | Statement: [Katharina von Bora, placeOfBirth, Lippendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lippendorf Context triple: [Katharina von Bora, placeOfBirth, Lippendorf]
-
A.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
-
B.
Schkopau
Schkopau is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its large chemical industry complex.
-
C.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
D.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
E.
Friedrichsdorf
Friedrichsdorf is a town in the German state of Hesse, located north of Frankfurt and known historically for its Huguenot heritage and proximity to the Taunus mountains.
- 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: Lippendorf Triple: [Katharina von Bora, placeOfBirth, Lippendorf]
Generated description
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lippendorf Target entity description: Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
-
A.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
-
B.
Schkopau
Schkopau is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its large chemical industry complex.
-
C.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
D.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
E.
Friedrichsdorf
Friedrichsdorf is a town in the German state of Hesse, located north of Frankfurt and known historically for its Huguenot heritage and proximity to the Taunus mountains.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8812d808190b794862287a76c16 |
completed | March 7, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc027578c8190b830f550c45ceddc |
completed | March 10, 2026, 6:54 a.m. |
| NEDg | Description generation | batch_69afc0d32d5881908b80e0bfca5cd873 |
completed | March 10, 2026, 6:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc133f8088190bd505db0d0d1d6f7 |
completed | March 10, 2026, 6:59 a.m. |
Created at: March 6, 2026, 9:50 p.m.