Triple
T2972843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Benz |
E80320
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Benz
Benz is a German surname most famously associated with Karl Benz, the pioneering engineer and inventor of the first practical automobile.
|
E11202
|
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: Benz | Statement: [Karl Benz, familyName, Benz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benz Context triple: [Karl Benz, familyName, Benz]
-
A.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
B.
Spragga Benz
Spragga Benz is a prominent Jamaican dancehall deejay known for his influential 1990s hits and collaborations across reggae, hip hop, and international pop music.
-
C.
Mercedes-Benz
Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
-
D.
Mercedes
Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
-
E.
Mack
Mack is a given name commonly used as a masculine first name or nickname in English-speaking countries.
- 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: Benz Triple: [Karl Benz, familyName, Benz]
Generated description
Benz is a German surname most famously associated with Karl Benz, the pioneering engineer and inventor of the first practical automobile.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Benz Target entity description: Benz is a German surname most famously associated with Karl Benz, the pioneering engineer and inventor of the first practical automobile.
-
A.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
B.
Spragga Benz
Spragga Benz is a prominent Jamaican dancehall deejay known for his influential 1990s hits and collaborations across reggae, hip hop, and international pop music.
-
C.
Mercedes-Benz
chosen
Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
-
D.
Mercedes
Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
-
E.
Mack
Mack is a given name commonly used as a masculine first name or nickname in English-speaking countries.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad998656948190ba79d7196d735f34 |
completed | March 8, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fca910e481909c1d93b512a779aa |
completed | March 11, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69b1005d34a081909ed24a3ac823f375 |
completed | March 11, 2026, 5:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b101078adc819095b0951e0c35cc3e |
completed | March 11, 2026, 5:43 a.m. |
Created at: March 8, 2026, 2:58 p.m.