Triple
T12466348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eifel (Belgium) |
E297934
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Weismes
Weismes is a municipality and village in the German-speaking region of eastern Belgium, known for its location in the hilly Eifel area near the High Fens nature reserve.
|
E984727
|
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: Weismes | Statement: [Eifel (Belgium), hasSettlement, Weismes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weismes Context triple: [Eifel (Belgium), hasSettlement, Weismes]
-
A.
Weis
Weis is a surname most prominently associated with Charlie Weis, an American football coach known for his tenure with the Notre Dame Fighting Irish and in the NFL.
-
B.
Weitzel
Weitzel is a surname of likely German or Dutch origin borne by individuals such as Edu Weitzel Douwes Dekker.
-
C.
Weichs
Weichs is a municipality in Bavaria, Germany, situated in the district of Dachau near Munich.
-
D.
Wasmer
Wasmer is a WebAssembly runtime that enables running WebAssembly modules efficiently across different platforms and programming languages.
-
E.
Weigel
Weigel is a German-language surname borne by various notable figures in fields such as science, the arts, and public life.
- 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: Weismes Triple: [Eifel (Belgium), hasSettlement, Weismes]
Generated description
Weismes is a municipality and village in the German-speaking region of eastern Belgium, known for its location in the hilly Eifel area near the High Fens nature reserve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weismes Target entity description: Weismes is a municipality and village in the German-speaking region of eastern Belgium, known for its location in the hilly Eifel area near the High Fens nature reserve.
-
A.
Weis
Weis is a surname most prominently associated with Charlie Weis, an American football coach known for his tenure with the Notre Dame Fighting Irish and in the NFL.
-
B.
Weitzel
Weitzel is a surname of likely German or Dutch origin borne by individuals such as Edu Weitzel Douwes Dekker.
-
C.
Weichs
Weichs is a municipality in Bavaria, Germany, situated in the district of Dachau near Munich.
-
D.
Wasmer
Wasmer is a WebAssembly runtime that enables running WebAssembly modules efficiently across different platforms and programming languages.
-
E.
Weigel
Weigel is a German-language surname borne by various notable figures in fields such as science, the arts, and public life.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94db7828481909d8f02b2fde83567 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f1f44f481909c7efdffd2aeac41 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f641a309cc8190b2403e62a6acfe58 |
completed | May 2, 2026, 6:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6427c162c8190ae2c027913d43b9e |
completed | May 2, 2026, 6:29 p.m. |
Created at: April 8, 2026, 9:56 p.m.