Triple
T2972974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EQ |
E80322
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Mercedes me Charge |
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 me Charge | Statement: [EQ, associatedWith, Mercedes me Charge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mercedes me Charge Context triple: [EQ, associatedWith, Mercedes me Charge]
-
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.
Maxus
Maxus is a commercial vehicle brand known for producing vans, pickups, and light trucks, owned by the Chinese automotive giant SAIC Motor.
-
C.
Porsche Taycan
The Porsche Taycan is a high-performance all-electric luxury sports sedan known for its rapid acceleration, advanced technology, and Porsche’s signature driving dynamics.
-
D.
Mercedes-Benz
chosen
Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
-
E.
Ford Model e
Ford Model e is Ford Motor Company's dedicated division focused on developing and producing electric and connected vehicles.
- 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_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. |
Created at: March 8, 2026, 2:58 p.m.