Triple
T13180470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ursula |
E313707
|
entity |
| Predicate | isUsedBy |
P1480
|
FINISHED |
| Object |
Ursula Reit
Ursula Reit was a German actress best known for her role as Mrs. Gloop in the 1971 film "Willy Wonka & the Chocolate Factory."
|
E1035893
|
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: Ursula Reit | Statement: [Ursula, isUsedBy, Ursula Reit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ursula Reit Context triple: [Ursula, isUsedBy, Ursula Reit]
-
A.
Ursula Karven
Ursula Karven is a German actress, model, and yoga instructor known for her roles in German television series and films as well as for her popular yoga books and DVDs.
-
B.
Ursula Seiler-Ayçiçek
Ursula Seiler-Ayçiçek is a German local politician who serves as the mayor of the town of Herbrechtingen in Baden-Württemberg.
-
C.
Ursula Paetsch
Ursula Paetsch was the wife of German chess grandmaster Erich Hartmann.
-
D.
Ute Grunert
Ute Grunert is known as the spouse of Nobel Prize–winning German author Günter Grass.
-
E.
Elisabeth Röckel
Elisabeth Röckel was a 19th-century German soprano closely associated with the Viennese musical scene and figures such as Beethoven and her husband, composer Johann Nepomuk Hummel.
- 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: Ursula Reit Triple: [Ursula, isUsedBy, Ursula Reit]
Generated description
Ursula Reit was a German actress best known for her role as Mrs. Gloop in the 1971 film "Willy Wonka & the Chocolate Factory."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ursula Reit Target entity description: Ursula Reit was a German actress best known for her role as Mrs. Gloop in the 1971 film "Willy Wonka & the Chocolate Factory."
-
A.
Ursula Karven
Ursula Karven is a German actress, model, and yoga instructor known for her roles in German television series and films as well as for her popular yoga books and DVDs.
-
B.
Ursula Seiler-Ayçiçek
Ursula Seiler-Ayçiçek is a German local politician who serves as the mayor of the town of Herbrechtingen in Baden-Württemberg.
-
C.
Ursula Paetsch
Ursula Paetsch was the wife of German chess grandmaster Erich Hartmann.
-
D.
Ute Grunert
Ute Grunert is known as the spouse of Nobel Prize–winning German author Günter Grass.
-
E.
Elisabeth Röckel
Elisabeth Röckel was a 19th-century German soprano closely associated with the Viennese musical scene and figures such as Beethoven and her husband, composer Johann Nepomuk Hummel.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c490ed081908ea54edb25c3de90 |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f13a63c81909335c0a45c3f7eca |
completed | May 3, 2026, 10:10 a.m. |
| NEDg | Description generation | batch_69f7220def9081908335441ff5134444 |
completed | May 3, 2026, 10:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7228d90888190be3ad818cdb75ed9 |
completed | May 3, 2026, 10:25 a.m. |
Created at: April 9, 2026, 9:14 p.m.