Triple
T6294174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eckert |
E141088
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Astrid Eckert
Astrid Eckert is a historian and academic known for her work on modern German history, memory culture, and the legacy of the Cold War.
|
E587010
|
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: Astrid Eckert | Statement: [Eckert, hasNotableBearer, Astrid Eckert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Astrid Eckert Context triple: [Eckert, hasNotableBearer, Astrid Eckert]
-
A.
Nena von Schlebrügge
Nena von Schlebrügge is a Swedish-born former fashion model of German and Swedish descent who worked internationally in the 1950s and 1960s and is the mother of actress Uma Thurman.
-
B.
Eva Schubach
Eva Schubach is known as a former spouse of Gerhard Schröder, the one-time Chancellor of Germany.
-
C.
Gjertrud Schnackenberg
Gjertrud Schnackenberg is an American poet acclaimed for her intellectually rich, formally intricate verse and contributions to contemporary literature.
-
D.
Eva Huber
Eva Huber is a notable individual who shares the surname Huber, recognized enough to be specifically cited as a bearer of the name.
-
E.
Adelheid Wendt
Adelheid Wendt was the mother of renowned German conductor and composer Wilhelm Furtwängler.
- 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: Astrid Eckert Triple: [Eckert, hasNotableBearer, Astrid Eckert]
Generated description
Astrid Eckert is a historian and academic known for her work on modern German history, memory culture, and the legacy of the Cold War.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Astrid Eckert Target entity description: Astrid Eckert is a historian and academic known for her work on modern German history, memory culture, and the legacy of the Cold War.
-
A.
Nena von Schlebrügge
Nena von Schlebrügge is a Swedish-born former fashion model of German and Swedish descent who worked internationally in the 1950s and 1960s and is the mother of actress Uma Thurman.
-
B.
Eva Schubach
Eva Schubach is known as a former spouse of Gerhard Schröder, the one-time Chancellor of Germany.
-
C.
Gjertrud Schnackenberg
Gjertrud Schnackenberg is an American poet acclaimed for her intellectually rich, formally intricate verse and contributions to contemporary literature.
-
D.
Eva Huber
Eva Huber is a notable individual who shares the surname Huber, recognized enough to be specifically cited as a bearer of the name.
-
E.
Adelheid Wendt
Adelheid Wendt was the mother of renowned German conductor and composer Wilhelm Furtwängler.
- 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_69c008cdf2ac8190bb640c94478fb4ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06438654481908c9833c5f0d61773 |
completed | March 22, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c603f715a08190b44156b4f5166631 |
completed | March 27, 2026, 4:13 a.m. |
| NEDg | Description generation | batch_69c606901e488190825bf74f9997735f |
completed | March 27, 2026, 4:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c60706fcf48190a7327da1dbddf854 |
completed | March 27, 2026, 4:26 a.m. |
Created at: March 22, 2026, 4:27 p.m.