Triple
T25802532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Salak |
E649874
|
entity |
| Predicate | airAccidentSite |
P26084
|
FINISHED |
| Object | multiple Indonesian military aircraft crashes |
—
|
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: multiple Indonesian military aircraft crashes | Statement: [Mount Salak, airAccidentSite, multiple Indonesian military aircraft crashes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airAccidentSite Context triple: [Mount Salak, airAccidentSite, multiple Indonesian military aircraft crashes]
-
A.
aircraftAccident
Indicates that an event involves an aircraft experiencing an accident, such as a crash, collision, or serious malfunction during operation.
-
B.
planeCrashLocation
Indicates the location where a plane crash occurred.
-
C.
accidentAirport
Indicates the airport at which an accident involving the subject entity occurred.
-
D.
missionAccident
Indicates that an accident or unintended harmful event occurred during the course of a mission or operation.
-
E.
siteOfAccident
chosen
Indicates the location where an accident occurred.
- 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_69e7ab34f8c8819099f6c4dabdabf129 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5ffccd0d0819095d21378b5b9590a |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 22, 2026, 6:41 a.m.