Triple
T13228022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercedes-Benz EQC |
E314931
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
EQC
EQC is a fully electric luxury compact SUV produced by Mercedes-Benz as part of its EQ lineup of battery-electric vehicles.
|
E1028058
|
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: EQC | Statement: [Mercedes-Benz EQC, alsoKnownAs, EQC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EQC Context triple: [Mercedes-Benz EQC, alsoKnownAs, EQC]
-
A.
EQF
EQF is a European reference framework that helps compare and translate qualifications across different countries’ education and training systems.
-
B.
EQE
EQE is a fully electric executive sedan from Mercedes-Benz’s EQ lineup, positioned as a mid-size luxury alternative to the traditional E-Class.
-
C.
EQY
EQY is the IATA airport code for Charlotte–Monroe Executive Airport, a public airport serving the Monroe and greater Charlotte area in North Carolina, United States.
-
D.
EQA
EQA is Mercedes-Benz’s compact all-electric SUV designed as part of the brand’s EQ lineup of battery-powered vehicles.
-
E.
EQS
The EQS is Mercedes-Benz’s flagship all-electric luxury sedan, designed to showcase the brand’s cutting-edge technology, range, and comfort in the EV segment.
- 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: EQC Triple: [Mercedes-Benz EQC, alsoKnownAs, EQC]
Generated description
EQC is a fully electric luxury compact SUV produced by Mercedes-Benz as part of its EQ lineup of battery-electric vehicles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: EQC Target entity description: EQC is a fully electric luxury compact SUV produced by Mercedes-Benz as part of its EQ lineup of battery-electric vehicles.
-
A.
EQF
EQF is a European reference framework that helps compare and translate qualifications across different countries’ education and training systems.
-
B.
EQE
EQE is a fully electric executive sedan from Mercedes-Benz’s EQ lineup, positioned as a mid-size luxury alternative to the traditional E-Class.
-
C.
EQY
EQY is the IATA airport code for Charlotte–Monroe Executive Airport, a public airport serving the Monroe and greater Charlotte area in North Carolina, United States.
-
D.
EQA
EQA is Mercedes-Benz’s compact all-electric SUV designed as part of the brand’s EQ lineup of battery-powered vehicles.
-
E.
EQS
The EQS is Mercedes-Benz’s flagship all-electric luxury sedan, designed to showcase the brand’s cutting-edge technology, range, and comfort in the EV segment.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff2a4b0c8190a853a1f6f4d1cbaf |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f70099f98081909877392c9ec49766 |
completed | May 3, 2026, 8 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f702620bc881909d4348fd2c709232 |
completed | May 3, 2026, 8:08 a.m. |
Created at: April 9, 2026, 9:21 p.m.