Triple
T18169635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ansbach district |
E434988
|
entity |
| Predicate | hasHistoricTown |
P847
|
FINISHED |
| Object |
Herrieden
Herrieden is a historic small town in the Middle Franconia region of Bavaria, Germany, known for its well-preserved medieval character and location along the Altmühl River.
|
E1310039
|
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: Herrieden | Statement: [Ansbach district, hasHistoricTown, Herrieden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herrieden Context triple: [Ansbach district, hasHistoricTown, Herrieden]
-
A.
Heidenfeld
Heidenfeld is a village in Bavaria, Germany, known as the birthplace of Cardinal Michael von Faulhaber.
-
B.
Hagenborgh
Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
-
C.
Harksheide
Harksheide was a former municipality in Schleswig-Holstein, Germany, that later became part of the city of Norderstedt.
-
D.
Hepscheid
Hepscheid is a small village that forms part of the municipality of Amel in the German-speaking Community of eastern Belgium.
-
E.
Heerdt
Heerdt is a district of Düsseldorf, Germany, located on the left bank of the Rhine and characterized by a mix of residential, commercial, and industrial areas.
- 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: Herrieden Triple: [Ansbach district, hasHistoricTown, Herrieden]
Generated description
Herrieden is a historic small town in the Middle Franconia region of Bavaria, Germany, known for its well-preserved medieval character and location along the Altmühl River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Herrieden Target entity description: Herrieden is a historic small town in the Middle Franconia region of Bavaria, Germany, known for its well-preserved medieval character and location along the Altmühl River.
-
A.
Heidenfeld
Heidenfeld is a village in Bavaria, Germany, known as the birthplace of Cardinal Michael von Faulhaber.
-
B.
Hagenborgh
Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
-
C.
Harksheide
Harksheide was a former municipality in Schleswig-Holstein, Germany, that later became part of the city of Norderstedt.
-
D.
Hepscheid
Hepscheid is a small village that forms part of the municipality of Amel in the German-speaking Community of eastern Belgium.
-
E.
Heerdt
Heerdt is a district of Düsseldorf, Germany, located on the left bank of the Rhine and characterized by a mix of residential, commercial, and industrial areas.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df555af081908a2f12bce6a13f56 |
completed | April 19, 2026, 1:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a038fc6c5008190a5ade67801d6df75 |
completed | May 12, 2026, 8:38 p.m. |
| NEDg | Description generation | batch_6a03914c5f6081908963548dc01a524a |
completed | May 12, 2026, 8:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03925c322081909d435251e869194d |
completed | May 12, 2026, 8:49 p.m. |
Created at: April 10, 2026, 10:30 a.m.