Triple
T14698846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marius Weyers |
E345235
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Weyers
Weyers is a Germanic-origin surname borne by various individuals, including the South African actor Marius Weyers.
|
E1113747
|
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: Weyers | Statement: [Marius Weyers, familyName, Weyers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weyers Context triple: [Marius Weyers, familyName, Weyers]
-
A.
Weyer
Weyer is a village and district within the town of Mechernich in the Euskirchen district of North Rhine-Westphalia, Germany.
-
B.
Weitzel
Weitzel is a surname of likely German or Dutch origin borne by individuals such as Edu Weitzel Douwes Dekker.
-
C.
Niederweyer
Niederweyer is a village-level district that forms part of the town of Hadamar in the German state of Hesse.
-
D.
Weisendorf
Weisendorf is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its rural character and proximity to the city of Erlangen.
-
E.
Welper
Welper is a district of the town of Hattingen in North Rhine-Westphalia, Germany.
- 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: Weyers Triple: [Marius Weyers, familyName, Weyers]
Generated description
Weyers is a Germanic-origin surname borne by various individuals, including the South African actor Marius Weyers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weyers Target entity description: Weyers is a Germanic-origin surname borne by various individuals, including the South African actor Marius Weyers.
-
A.
Weyer
Weyer is a village and district within the town of Mechernich in the Euskirchen district of North Rhine-Westphalia, Germany.
-
B.
Weitzel
Weitzel is a surname of likely German or Dutch origin borne by individuals such as Edu Weitzel Douwes Dekker.
-
C.
Niederweyer
Niederweyer is a village-level district that forms part of the town of Hadamar in the German state of Hesse.
-
D.
Weisendorf
Weisendorf is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its rural character and proximity to the city of Erlangen.
-
E.
Welper
Welper is a district of the town of Hattingen in North Rhine-Westphalia, Germany.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb604f88081908a677175045496d0 |
completed | April 14, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde19040e0819099159ed2609c6965 |
completed | May 8, 2026, 1:13 p.m. |
| NEDg | Description generation | batch_69fde43698e881908226ae4907910249 |
completed | May 8, 2026, 1:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fde53290a48190b3701472bb4e3d63 |
completed | May 8, 2026, 1:29 p.m. |
Created at: April 10, 2026, 1:28 a.m.