Triple
T13442888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercédès Jellinek |
E320408
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Jellinek
Jellinek is a surname most famously associated with Mercédès Jellinek, the namesake of the Mercedes automobile brand.
|
E320409
|
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: Jellinek | Statement: [Mercédès Jellinek, familyName, Jellinek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jellinek Context triple: [Mercédès Jellinek, familyName, Jellinek]
-
A.
Lilienfeld
Lilienfeld is a German-language surname most notably associated with physicist Julius Edgar Lilienfeld, an early pioneer of field-effect transistor concepts.
-
B.
Mayr
Mayr is a German surname most notably associated with Ernst Mayr, a pioneering evolutionary biologist and key architect of the modern synthesis in evolutionary theory.
-
C.
Frauenthal
Frauenthal is a historic theater and cultural landmark in Muskegon, Michigan, known for hosting a wide range of performing arts events.
-
D.
Feigl
Feigl is a German-language surname borne by various notable individuals, including philosophers, scientists, and artists.
-
E.
Meyer-Lübke
Meyer-Lübke is the surname of Wilhelm Meyer-Lübke, a prominent Swiss linguist known for his influential work in Romance philology.
- 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: Jellinek Triple: [Mercédès Jellinek, familyName, Jellinek]
Generated description
Jellinek is a surname most famously associated with Mercédès Jellinek, the namesake of the Mercedes automobile brand.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jellinek Target entity description: Jellinek is a surname most famously associated with Mercédès Jellinek, the namesake of the Mercedes automobile brand.
-
A.
Jellinek
chosen
Jellinek is a surname most notably associated with Mercedes Jellinek, the namesake and inspiration for the Mercedes automobile brand.
-
B.
Blanka Jellinek
Blanka Jellinek was a member of the Jellinek family, historically associated with the early development and naming of the Mercedes automobile brand.
-
C.
Helene Jellinek
Helene Jellinek was a member of the Jellinek family associated with the early history of the Mercedes automobile brand.
-
D.
Johanna Jellinek
Johanna Jellinek was a member of the Jellinek family, historically associated with the origins of the Mercedes automobile brand.
-
E.
Mira Jellinek
Mira Jellinek was a member of the Jellinek family associated with the early history of the Mercedes automobile brand, known primarily as the sister of Mercedes Jellinek.
- F. None of above.
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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee881888190811ddf01bc699864 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739965ef081909e85881ce805bbb5 |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f740e536d48190af369b38aa42438d |
completed | May 3, 2026, 12:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f741b72d08819087808bf9bcffa0a1 |
completed | May 3, 2026, 12:38 p.m. |
Created at: April 9, 2026, 9:40 p.m.