Triple
T16835267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hrabove |
E409257
|
entity |
| Predicate | nearbyCrashConflictContext |
P125033
|
FINISHED |
| Object | war in Donbas |
—
|
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: war in Donbas | Statement: [Hrabove, nearbyCrashConflictContext, war in Donbas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCrashConflictContext Context triple: [Hrabove, nearbyCrashConflictContext, war in Donbas]
-
A.
occursNear
Indicates that one event or entity takes place or exists in close spatial proximity to another.
-
B.
hasNearbyCrossingPoint
Indicates that one location has a crossing point (such as a bridge, crosswalk, or intersection) situated close to it.
-
C.
crossesNear
Indicates that one entity passes across the path or area of another entity at a location that is close to, but not directly intersecting, the other entity.
-
D.
hasAtGradeCrossingNearby
Indicates that one entity (typically a location or segment) has a nearby at-grade crossing where two transportation paths intersect at the same level.
-
E.
nearbyInfluence
Indicates that one entity affects or exerts influence on another due to being physically or spatially close to it.
- 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_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. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:23 a.m.