Triple
T30521604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autodromo Internazionale Enzo e Dino Ferrari |
E776705
|
entity |
| Predicate | sceneOfFatalAccident |
P26084
|
FINISHED |
| Object | Ayrton Senna |
—
|
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: Ayrton Senna | Statement: [Autodromo Internazionale Enzo e Dino Ferrari, sceneOfFatalAccident, Ayrton Senna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneOfFatalAccident Context triple: [Autodromo Internazionale Enzo e Dino Ferrari, sceneOfFatalAccident, Ayrton Senna]
-
A.
siteOfAccident
chosen
Indicates the location where an accident occurred.
-
B.
fatalAccident
Indicates that an accident resulted in at least one death.
-
C.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
D.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
-
E.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
- F. None of above.
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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6880b4a788190b7031f48ee4daf3a |
completed | May 2, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:17 p.m.