Triple
T20814026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northrop M2-F2 |
E512387
|
entity |
| Predicate | crashResult |
P66762
|
FINISHED |
| Object | airframe heavily damaged |
—
|
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: airframe heavily damaged | Statement: [Northrop M2-F2, crashResult, airframe heavily damaged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crashResult Context triple: [Northrop M2-F2, crashResult, airframe heavily damaged]
-
A.
crashResultedIn
chosen
Indicates that a crash event caused or led to a particular outcome, consequence, or result.
-
B.
crashCountry
Indicates that an aviation crash event occurred within the territory or jurisdiction of a specified country.
-
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.
crashSiteRegion
Indicates the geographic region in which a crash site is located.
-
E.
deathResult
Indicates that one event, condition, or action leads to or causes the death of an entity.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d4e43c8190aecce82a3f7e2de0 |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:40 p.m.