Triple
T2978098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Formula One |
E80445
|
entity |
| Predicate | notableConstructor |
P44379
|
FINISHED |
| Object | Mercedes |
E11202
|
NE FINISHED |
How this triple was built (2 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: Mercedes | Statement: [Formula One, notableConstructor, Mercedes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mercedes Context triple: [Formula One, notableConstructor, Mercedes]
-
A.
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."
-
B.
Mercedes-Benz
chosen
Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
-
C.
Porsche
Porsche is a German luxury automobile manufacturer renowned for its high-performance sports cars, SUVs, and engineering excellence.
-
D.
Haas
Haas is a German-origin surname borne by numerous individuals worldwide, including several notable figures in fields such as sports, science, and the arts.
-
E.
Mercedes-Benz USA
Mercedes-Benz USA is the American subsidiary of the German luxury automobile manufacturer Mercedes-Benz, responsible for marketing, sales, and distribution of its vehicles in the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9e11c4188190a3ae8fd0cbd8c2c0 |
completed | March 8, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360881c9081909cb4c5e7b93d7b78 |
completed | March 13, 2026, 12:55 a.m. |
Created at: March 8, 2026, 2:58 p.m.