Triple
T8045058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arras |
E187526
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object |
Oudenburg
Oudenburg is a small historic town in the Belgian province of West Flanders, known for its Roman heritage and medieval abbey.
|
E706901
|
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: Oudenburg | Statement: [Arras, twinTown, Oudenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oudenburg Context triple: [Arras, twinTown, Oudenburg]
-
A.
Blankenburg
Blankenburg is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and village-like atmosphere.
-
B.
Blankenburg
Blankenburg is a town in central Germany, located in the Harz region of the state of Saxony-Anhalt.
-
C.
Kronenburg
Kronenburg is a tram and metro stop in Amstelveen, Netherlands, serving the Amsterdam metro/Tram 25 line and the surrounding residential and commercial area.
-
D.
Oldenburg
Oldenburg is a historic university city in northwestern Germany known for its cultural heritage and role as a regional economic center.
-
E.
Oldenburg
Oldenburg is a historic European noble house that ruled various territories in Denmark, Norway, and northern Germany and provided numerous monarchs to several European thrones.
- 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: Oudenburg Triple: [Arras, twinTown, Oudenburg]
Generated description
Oudenburg is a small historic town in the Belgian province of West Flanders, known for its Roman heritage and medieval abbey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oudenburg Target entity description: Oudenburg is a small historic town in the Belgian province of West Flanders, known for its Roman heritage and medieval abbey.
-
A.
Blankenburg
Blankenburg is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and village-like atmosphere.
-
B.
Blankenburg
Blankenburg is a town in central Germany, located in the Harz region of the state of Saxony-Anhalt.
-
C.
Kronenburg
Kronenburg is a tram and metro stop in Amstelveen, Netherlands, serving the Amsterdam metro/Tram 25 line and the surrounding residential and commercial area.
-
D.
Oldenburg
Oldenburg is a historic university city in northwestern Germany known for its cultural heritage and role as a regional economic center.
-
E.
Oldenburg
Oldenburg is a historic European noble house that ruled various territories in Denmark, Norway, and northern Germany and provided numerous monarchs to several European thrones.
- 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_69ca82b00cb48190b59a300f70e97bd7 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f4c79388190aecee6e313071a17 |
completed | March 31, 2026, 3:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc570cfad08190a8ed35ef2a47f497 |
completed | March 31, 2026, 11:21 p.m. |
| NEDg | Description generation | batch_69cc58acba3c8190b7d09aa23b5f10f8 |
completed | March 31, 2026, 11:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc5cc9161c8190aae90f453f6d98c0 |
completed | March 31, 2026, 11:46 p.m. |
Created at: March 30, 2026, 5:24 p.m.