Triple
T921376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Lippe |
E19891
|
entity |
| Predicate | ruledFrom |
P6175
|
FINISHED |
| Object |
Detmold
Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
|
E269423
|
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: Detmold | Statement: [House of Lippe, ruledFrom, Detmold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Detmold Context triple: [House of Lippe, ruledFrom, Detmold]
-
A.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
B.
Osnabrück
Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
-
C.
Kleve
Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
-
D.
Hildesheim
Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
-
E.
Recklinghausen
Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
- 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: Detmold Triple: [House of Lippe, ruledFrom, Detmold]
Generated description
Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Detmold Target entity description: Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
-
A.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
B.
Osnabrück
Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
-
C.
Kleve
Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
-
D.
Hildesheim
Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
-
E.
Recklinghausen
Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b313cb908190ad78b3a54e4f2eb7 |
completed | March 1, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1731ebe481908ffd1a670ae86286 |
completed | March 9, 2026, 6:53 p.m. |
| NEDg | Description generation | batch_69af188b0dfc819085d3b923b204f03e |
completed | March 9, 2026, 6:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af191a14348190851ee44d3dbc20e3 |
completed | March 9, 2026, 7:01 p.m. |
Created at: March 1, 2026, 7:40 p.m.