Triple
T17455753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reno Air Races |
E425022
|
entity |
| Predicate | 2011AccidentFatalities |
P127534
|
FINISHED |
| Object | over 10 people killed including the pilot |
—
|
LITERAL 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: over 10 people killed including the pilot | Statement: [Reno Air Races, 2011AccidentFatalities, over 10 people killed including the pilot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 2011AccidentFatalities Context triple: [Reno Air Races, 2011AccidentFatalities, over 10 people killed including the pilot]
-
A.
numberOfFatalAccidents
Indicates the total count of accidents within a given context that resulted in at least one fatality.
-
B.
constructionAccidentFatalities
Indicates that a construction-related accident resulted in one or more fatalities.
-
C.
fatalAccident
Indicates that an accident resulted in at least one death.
-
D.
notableAccidentYear
Indicates the year in which a notable accident involving the subject occurred.
-
E.
aircraftAccidentYear
Indicates the calendar year in which an aircraft accident occurred.
- F. None of above. chosen
Provenance (4 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45141e1d48190b7de9159f1fd71fa |
completed | April 19, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f0e3fc819094e466b74622c956 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:47 a.m.