Triple
T19193431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferrari Purosangue |
E469900
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Ferrari |
—
|
NE NERFINISHED |
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: Ferrari | Statement: [Ferrari Purosangue, brand, Ferrari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ferrari Context triple: [Ferrari Purosangue, brand, Ferrari]
-
A.
Ferrari
chosen
Ferrari is an Italian luxury sports car manufacturer renowned for its high-performance vehicles, racing heritage, and iconic prancing horse emblem.
-
B.
Ferrari
"Ferrari" is a popular Afropop song by Nigerian singer Yemi Alade, known for its catchy melody and lyrics about love and material commitment.
-
C.
Maserati
Maserati is an Italian luxury automobile manufacturer renowned for its high-performance sports cars and grand tourers distinguished by elegant design and racing heritage.
-
D.
Lamborghini
Lamborghini is an Italian luxury sports car manufacturer renowned for its high-performance, aggressively styled supercars and exotic design.
-
E.
Alfa Romeo
Alfa Romeo is an Italian automobile manufacturer renowned for its sporty, stylish cars and long heritage in motorsport and performance engineering.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f8a409948190a17aa28a6e9c8844 |
completed | April 20, 2026, 9:57 a.m. |
Created at: April 10, 2026, 12:07 p.m.