Triple
T4106630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daimler AG |
E88466
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Smart |
E80321
|
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: Smart | Statement: [Daimler AG, brand, Smart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smart Context triple: [Daimler AG, brand, Smart]
-
A.
smart
chosen
smart is an automotive marque best known for its compact city cars and microcars, originally developed in partnership with Swatch and later owned by Mercedes-Benz.
-
B.
Smartism
Smartism is a major Hindu tradition that emphasizes the worship of multiple deities as different manifestations of the one ultimate reality, often centered on Advaita Vedanta philosophy.
-
C.
Get Smart
Get Smart is a 2008 action-comedy film adaptation of the classic TV series, starring Steve Carell as an inept secret agent alongside Anne Hathaway.
-
D.
SmartLess
SmartLess is a popular comedy podcast featuring candid, humorous interviews with celebrities and public figures, co-hosted by actors Will Arnett, Jason Bateman, and Sean Hayes.
-
E.
Wise
Wise is a surname shared by various notable individuals across fields such as entertainment, politics, and academia.
- 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_69aed9484fb881909146f4c772ad277c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af019c7a3c8190a503ce80e87dc3b3 |
completed | March 9, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b7f88948190b87242e706a488c0 |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:40 p.m.