Triple
T16835266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hrabove |
E409257
|
entity |
| Predicate | nearbyCrashCause |
P8203
|
FINISHED |
| Object | airliner shot down by surface-to-air missile |
—
|
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: airliner shot down by surface-to-air missile | Statement: [Hrabove, nearbyCrashCause, airliner shot down by surface-to-air missile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCrashCause Context triple: [Hrabove, nearbyCrashCause, airliner shot down by surface-to-air missile]
-
A.
causedAccident
Indicates that one entity is responsible for bringing about or initiating an accident involving another entity or situation.
-
B.
breaksDownNear
Indicates that one entity ceases to function or fails in close spatial proximity to another entity or location.
-
C.
associatedCrashSite
Indicates that an entity is linked or related to a particular crash site, typically as the site where an incident involving that entity occurred or is recorded.
-
D.
siteOfAccident
Indicates the location where an accident occurred.
-
E.
occursNear
chosen
Indicates that one event or entity takes place or exists in close spatial proximity to another.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b31aa44c8190b4f402f1898e6998 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:23 a.m.