Triple
T15516329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tasha Schwikert |
E368842
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Schwikert
Schwikert is the surname of American artistic gymnast Tasha Schwikert, a prominent member of the U.S. national team in the early 2000s.
|
E1162020
|
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: Schwikert | Statement: [Tasha Schwikert, familyName, Schwikert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwikert Context triple: [Tasha Schwikert, familyName, Schwikert]
-
A.
Werneck
Werneck is a market town in the Schweinfurt district of northern Bavaria, Germany, known for its baroque palace and surrounding rural landscape.
-
B.
Sven Wagner
Sven Wagner is a German local politician who serves as the mayor of the town of Aschersleben in Saxony-Anhalt.
-
C.
Dirk Wilutzky
Dirk Wilutzky is a German film producer and director best known for his work on the Academy Award–winning documentary "Citizenfour."
-
D.
Matthias Weckmann
Matthias Weckmann was a 17th-century German composer and organist known for his expressive sacred music and significant contributions to the North German organ tradition.
-
E.
Schrempf
Schrempf is a German surname most notably associated with former NBA basketball player Detlef Schrempf.
- 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: Schwikert Triple: [Tasha Schwikert, familyName, Schwikert]
Generated description
Schwikert is the surname of American artistic gymnast Tasha Schwikert, a prominent member of the U.S. national team in the early 2000s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schwikert Target entity description: Schwikert is the surname of American artistic gymnast Tasha Schwikert, a prominent member of the U.S. national team in the early 2000s.
-
A.
Werneck
Werneck is a market town in the Schweinfurt district of northern Bavaria, Germany, known for its baroque palace and surrounding rural landscape.
-
B.
Sven Wagner
Sven Wagner is a German local politician who serves as the mayor of the town of Aschersleben in Saxony-Anhalt.
-
C.
Dirk Wilutzky
Dirk Wilutzky is a German film producer and director best known for his work on the Academy Award–winning documentary "Citizenfour."
-
D.
Matthias Weckmann
Matthias Weckmann was a 17th-century German composer and organist known for his expressive sacred music and significant contributions to the North German organ tradition.
-
E.
Schrempf
Schrempf is a German surname most notably associated with former NBA basketball player Detlef Schrempf.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04033303c8190a87b6384f68a6921 |
completed | April 16, 2026, 1:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d5111648190a61fc87170b0d93c |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff3f075bb881908c254137ca7c3f9f |
completed | May 9, 2026, 2:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff3f87f788819080eccae52b0df145 |
completed | May 9, 2026, 2:07 p.m. |
Created at: April 10, 2026, 4:02 a.m.