Triple
T7010096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dodge Hornet |
E162557
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Mazda CX-30 |
E396579
|
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: Mazda CX-30 | Statement: [Dodge Hornet, competitor, Mazda CX-30]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mazda CX-30 Context triple: [Dodge Hornet, competitor, Mazda CX-30]
-
A.
Mazda CX-30
chosen
The Mazda CX-30 is a compact crossover SUV known for its sleek design, upscale interior, and engaging driving dynamics within Mazda’s lineup.
-
B.
Mazda CX-5
The Mazda CX-5 is a compact crossover SUV known for its stylish design, engaging driving dynamics, and efficient Skyactiv technology.
-
C.
Mazda3
The Mazda3 is a popular compact car known for its sporty handling, stylish design, and well-appointed interior.
-
D.
Mazda2
The Mazda2 is a subcompact car known for its agile handling, fuel efficiency, and stylish design, positioned as an affordable entry-level model in Mazda’s lineup.
-
E.
Mitsubishi Eclipse Cross
The Mitsubishi Eclipse Cross is a compact crossover SUV known for its distinctive coupe-like styling, turbocharged performance, and position as a global model in Mitsubishi’s modern lineup.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc3917c481909a288c3e56630c48 |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a47aa6481908ac0039b2b728edb |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:34 p.m.