Triple
T15969065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porta Westfalica |
E387271
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object |
Nammen
Nammen is a former municipality in North Rhine-Westphalia, Germany, that was incorporated into the town of Porta Westfalica.
|
E1186275
|
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: Nammen | Statement: [Porta Westfalica, formedByMergerOf, Nammen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nammen Context triple: [Porta Westfalica, formedByMergerOf, Nammen]
-
A.
Copenhaver
Copenhaver is a surname of likely English or German origin borne by various individuals, including Eleanor Copenhaver.
-
B.
Grenaa
Grenaa is a coastal town in eastern Jutland, Denmark, known for its ferry connections to the island of Anholt and its role as a regional commercial and educational center.
-
C.
Skanderborg
Skanderborg is a Danish town in Jutland known for its lakeside setting and annual music festival, Smukfest.
-
D.
Emdrup
Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
-
E.
Sydhavn
Sydhavn is a district in Copenhagen, Denmark, known for its former industrial harbor areas now undergoing redevelopment into residential and commercial neighborhoods.
- 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: Nammen Triple: [Porta Westfalica, formedByMergerOf, Nammen]
Generated description
Nammen is a former municipality in North Rhine-Westphalia, Germany, that was incorporated into the town of Porta Westfalica.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nammen Target entity description: Nammen is a former municipality in North Rhine-Westphalia, Germany, that was incorporated into the town of Porta Westfalica.
-
A.
Copenhaver
Copenhaver is a surname of likely English or German origin borne by various individuals, including Eleanor Copenhaver.
-
B.
Grenaa
Grenaa is a coastal town in eastern Jutland, Denmark, known for its ferry connections to the island of Anholt and its role as a regional commercial and educational center.
-
C.
Skanderborg
Skanderborg is a Danish town in Jutland known for its lakeside setting and annual music festival, Smukfest.
-
D.
Emdrup
Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
-
E.
Sydhavn
Sydhavn is a district in Copenhagen, Denmark, known for its former industrial harbor areas now undergoing redevelopment into residential and commercial neighborhoods.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572847f08190830e30125e829766 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe88fa308190942d37cf67458396 |
completed | May 9, 2026, 11:08 p.m. |
| NEDg | Description generation | batch_69ffbf3f40288190a59646124e06a864 |
completed | May 9, 2026, 11:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffbfddd0348190baab794f613c71bf |
completed | May 9, 2026, 11:14 p.m. |
Created at: April 10, 2026, 4:54 a.m.