Triple
T21287761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diepholz district |
E524705
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Harpstedt
Harpstedt is a small municipality and administrative center in Lower Saxony, Germany, known for its rural character and location within the Diepholz district.
|
E1481507
|
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: Harpstedt | Statement: [Diepholz district, contains, Harpstedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harpstedt Context triple: [Diepholz district, contains, Harpstedt]
-
A.
Harkstede
Harkstede is a village in the Dutch province of Groningen, known for its rural character and proximity to the city of Groningen.
-
B.
Weickede
Weickede is a village-level subdivision of the town of Rüthen in the district of Soest, North Rhine-Westphalia, Germany.
-
C.
Wolmirstedt
Wolmirstedt is a small town in the German state of Saxony-Anhalt, located near Magdeburg and known for its historical town center and regional administrative role.
-
D.
Hettstedt
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
E.
Hummelsbüttel
Hummelsbüttel is a residential quarter in the borough of Wandsbek in Hamburg, Germany, known for its green spaces and suburban character.
- 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: Harpstedt Triple: [Diepholz district, contains, Harpstedt]
Generated description
Harpstedt is a small municipality and administrative center in Lower Saxony, Germany, known for its rural character and location within the Diepholz district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harpstedt Target entity description: Harpstedt is a small municipality and administrative center in Lower Saxony, Germany, known for its rural character and location within the Diepholz district.
-
A.
Harkstede
Harkstede is a village in the Dutch province of Groningen, known for its rural character and proximity to the city of Groningen.
-
B.
Weickede
Weickede is a village-level subdivision of the town of Rüthen in the district of Soest, North Rhine-Westphalia, Germany.
-
C.
Wolmirstedt
Wolmirstedt is a small town in the German state of Saxony-Anhalt, located near Magdeburg and known for its historical town center and regional administrative role.
-
D.
Hettstedt
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
E.
Hummelsbüttel
Hummelsbüttel is a residential quarter in the borough of Wandsbek in Hamburg, Germany, known for its green spaces and suburban character.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d7c57c8190bc4180ea590a62d4 |
completed | April 21, 2026, 8:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09b41017e081908e1c49faefddf65b |
completed | May 17, 2026, 12:26 p.m. |
| NEDg | Description generation | batch_6a09b6c4ad7c819088fddeb96f1848f1 |
completed | May 17, 2026, 12:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09b754528c81908af8205ff3cf334e |
completed | May 17, 2026, 12:40 p.m. |
Created at: April 16, 2026, 4:03 p.m.