Triple
T19878492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Arenberg |
E477702
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Arenberg
Arenberg is a historic town in western Germany that served as the administrative center of the former County of Arenberg.
|
E477700
|
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: Arenberg | Statement: [County of Arenberg, capital, Arenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arenberg Context triple: [County of Arenberg, capital, Arenberg]
-
A.
Arenberg
Arenberg is a historic town in western Germany that served as the political and administrative center of the former Duchy of Arenberg.
-
B.
Arenenberg
Arenenberg is a historic estate on the shores of Lake Constance in Switzerland, best known as the residence and later death place of Queen Hortense de Beauharnais and a key site of Napoleonic-era history.
-
C.
Livarchamps
Livarchamps is a small village in the municipality of Vaux-sur-Sûre in the Walloon region of Belgium.
-
D.
Chavignol
Chavignol is a small village in France’s Loire Valley renowned for its traditional goat’s milk cheese, Crottin de Chavignol.
-
E.
Arroux
Arroux is a river in central France that flows through the Burgundy region before joining the Loire.
- 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: Arenberg Triple: [County of Arenberg, capital, Arenberg]
Generated description
Arenberg is a historic town in western Germany that served as the administrative center of the former County of Arenberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arenberg Target entity description: Arenberg is a historic town in western Germany that served as the administrative center of the former County of Arenberg.
-
A.
Arenberg
chosen
Arenberg is a historic town in western Germany that served as the political and administrative center of the former Duchy of Arenberg.
-
B.
Arenenberg
Arenenberg is a historic estate on the shores of Lake Constance in Switzerland, best known as the residence and later death place of Queen Hortense de Beauharnais and a key site of Napoleonic-era history.
-
C.
Livarchamps
Livarchamps is a small village in the municipality of Vaux-sur-Sûre in the Walloon region of Belgium.
-
D.
Chavignol
Chavignol is a small village in France’s Loire Valley renowned for its traditional goat’s milk cheese, Crottin de Chavignol.
-
E.
Arroux
Arroux is a river in central France that flows through the Burgundy region before joining the Loire.
- F. None of above.
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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658dc8ce08190b005ad49924e5659 |
completed | April 20, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07dbc82f0881909556c54b8ce3533f |
completed | May 16, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_6a07dc854a0c8190b0da81ead6b9cfc1 |
completed | May 16, 2026, 2:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07dd45e93c8190b14c23487398a8ec |
completed | May 16, 2026, 2:58 a.m. |
Created at: April 10, 2026, 1:52 p.m.