Triple
T14525651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Wohlers |
E340768
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Wohlers
Wohlers is a German-origin surname borne by various notable individuals, including athletes and professionals.
|
E1104612
|
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: Wohlers | Statement: [Mark Wohlers, familyName, Wohlers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wohlers Context triple: [Mark Wohlers, familyName, Wohlers]
-
A.
Worner
Worner is a surname and variant spelling of "Warner," used by various individuals and families, particularly in English-speaking countries.
-
B.
Weller
Weller is a surname most prominently associated with English singer-songwriter and musician Paul Weller.
-
C.
Wolthusen
Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
-
D.
Rohrer
Rohrer is a surname most notably associated with Swiss physicist Heinrich Rohrer, co-inventor of the scanning tunneling microscope and Nobel Prize laureate.
-
E.
Stottlemeyer
Stottlemeyer is the surname of Captain Leland Stottlemeyer, a central police character from the television series "Monk."
- 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: Wohlers Triple: [Mark Wohlers, familyName, Wohlers]
Generated description
Wohlers is a German-origin surname borne by various notable individuals, including athletes and professionals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wohlers Target entity description: Wohlers is a German-origin surname borne by various notable individuals, including athletes and professionals.
-
A.
Worner
Worner is a surname and variant spelling of "Warner," used by various individuals and families, particularly in English-speaking countries.
-
B.
Weller
Weller is a surname most prominently associated with English singer-songwriter and musician Paul Weller.
-
C.
Wolthusen
Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
-
D.
Rohrer
Rohrer is a surname most notably associated with Swiss physicist Heinrich Rohrer, co-inventor of the scanning tunneling microscope and Nobel Prize laureate.
-
E.
Stottlemeyer
Stottlemeyer is the surname of Captain Leland Stottlemeyer, a central police character from the television series "Monk."
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea050781881909ed685d94479bf99 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a50324481909713bbf68295e839 |
completed | May 8, 2026, 5:53 a.m. |
| NEDg | Description generation | batch_69fd7c52e0bc8190b8c4b270653e65df |
completed | May 8, 2026, 6:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7cf3088c8190a3bf53c9599f0304 |
completed | May 8, 2026, 6:04 a.m. |
Created at: April 10, 2026, 1:22 a.m.