Triple
T11817401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holzminden |
E281035
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object |
Stadtoldendorf
Stadtoldendorf is a small town in Lower Saxony, Germany, known for its location in the Weser Uplands and its historic half-timbered architecture.
|
E948124
|
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: Stadtoldendorf | Statement: [Holzminden, hasNeighbouringMunicipality, Stadtoldendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stadtoldendorf Context triple: [Holzminden, hasNeighbouringMunicipality, Stadtoldendorf]
-
A.
Stadtallendorf
Stadtallendorf is a town in the German state of Hesse known for its industrial history and role as a regional economic center.
-
B.
Allendorf
Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, Germany.
-
C.
Nordendorf
Nordendorf is a small municipality in Bavaria, Germany, situated within the Augsburg district.
-
D.
Westendorf
Westendorf is a popular Austrian alpine village known for its skiing, hiking, and picturesque mountain scenery.
-
E.
Eltersdorf
Eltersdorf is a district of the Bavarian city of Erlangen in Germany, known for its residential character and local transport connections.
- 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: Stadtoldendorf Triple: [Holzminden, hasNeighbouringMunicipality, Stadtoldendorf]
Generated description
Stadtoldendorf is a small town in Lower Saxony, Germany, known for its location in the Weser Uplands and its historic half-timbered architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stadtoldendorf Target entity description: Stadtoldendorf is a small town in Lower Saxony, Germany, known for its location in the Weser Uplands and its historic half-timbered architecture.
-
A.
Stadtallendorf
Stadtallendorf is a town in the German state of Hesse known for its industrial history and role as a regional economic center.
-
B.
Allendorf
Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, Germany.
-
C.
Nordendorf
Nordendorf is a small municipality in Bavaria, Germany, situated within the Augsburg district.
-
D.
Westendorf
Westendorf is a popular Austrian alpine village known for its skiing, hiking, and picturesque mountain scenery.
-
E.
Eltersdorf
Eltersdorf is a district of the Bavarian city of Erlangen in Germany, known for its residential character and local transport connections.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5e760988190b50d13bba5ef5b43 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f131cbf9708190ba8394fb3508b975 |
completed | April 28, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_69f14e8a1b788190a1704d6e102342e3 |
completed | April 29, 2026, 12:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f15715a1588190ba0ec21647adc57c |
completed | April 29, 2026, 12:55 a.m. |
Created at: April 8, 2026, 9:42 p.m.