Triple
T13503104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudolf Uhlenhaut |
E320941
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Uhlenhaut
Uhlenhaut is a German surname most notably associated with Rudolf Uhlenhaut, a renowned automotive engineer for Mercedes-Benz.
|
E1044930
|
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: Uhlenhaut | Statement: [Rudolf Uhlenhaut, familyName, Uhlenhaut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uhlenhaut Context triple: [Rudolf Uhlenhaut, familyName, Uhlenhaut]
-
A.
Dermide
Dermide was the short-lived son of French general Charles Leclerc and Pauline Bonaparte, making him a nephew of Napoleon Bonaparte.
-
B.
Pellice
The Pellice is a river in northwestern Italy that flows through the Piedmont region and contributes to the local hydrology of the Metropolitan City of Turin.
-
C.
Skin
"Skin" is a song by the Dutch Eurodance group Sylver, known for its melodic trance-influenced sound and emotional lyrics.
-
D.
Skin
"Skin" is a 2018 biographical drama film starring Jamie Bell as a former neo-Nazi trying to leave a violent white supremacist movement and rebuild his life.
-
E.
Skin
"Skin" is a studio album by American rock singer-songwriter Melissa Etheridge, known for its introspective lyrics and emotionally raw exploration of personal transformation.
- 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: Uhlenhaut Triple: [Rudolf Uhlenhaut, familyName, Uhlenhaut]
Generated description
Uhlenhaut is a German surname most notably associated with Rudolf Uhlenhaut, a renowned automotive engineer for Mercedes-Benz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Uhlenhaut Target entity description: Uhlenhaut is a German surname most notably associated with Rudolf Uhlenhaut, a renowned automotive engineer for Mercedes-Benz.
-
A.
Dermide
Dermide was the short-lived son of French general Charles Leclerc and Pauline Bonaparte, making him a nephew of Napoleon Bonaparte.
-
B.
Pellice
The Pellice is a river in northwestern Italy that flows through the Piedmont region and contributes to the local hydrology of the Metropolitan City of Turin.
-
C.
Skin
"Skin" is a song by the Dutch Eurodance group Sylver, known for its melodic trance-influenced sound and emotional lyrics.
-
D.
Skin
"Skin" is a 2018 biographical drama film starring Jamie Bell as a former neo-Nazi trying to leave a violent white supremacist movement and rebuild his life.
-
E.
Skin
"Skin" is a studio album by American rock singer-songwriter Melissa Etheridge, known for its introspective lyrics and emotionally raw exploration of personal transformation.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf810e248190a060481004503f96 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75489e9908190b133937b5e92732d |
completed | May 3, 2026, 1:58 p.m. |
| NEDg | Description generation | batch_69f7555173d08190be887e81c148192e |
completed | May 3, 2026, 2:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f756773b9c81908250ae7ffc2d8d99 |
completed | May 3, 2026, 2:06 p.m. |
Created at: April 9, 2026, 9:43 p.m.