Triple
T17179039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vostochny |
E416932
|
entity |
| Predicate | oppositeDirectionTerm |
P116628
|
FINISHED |
| Object | Zapadny |
—
|
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: Zapadny | Statement: [Vostochny, oppositeDirectionTerm, Zapadny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oppositeDirectionTerm Context triple: [Vostochny, oppositeDirectionTerm, Zapadny]
-
A.
hasOppositeDirectionTo
chosen
Indicates that one entity’s direction is exactly reversed or opposed to the direction of another entity.
-
B.
opposite
Indicates that one entity is positioned or oriented directly across from, or in a contrary or reverse relation to, another entity.
-
C.
opposedDirectionRegion
Indicates that one region is oriented in the exact opposite direction relative to another region.
-
D.
hasConceptualOpposite
Indicates that one entity represents a concept that is fundamentally opposed or contrary in meaning to the concept represented by another entity.
-
E.
oppositeNumber
Indicates that one number is the additive inverse of the other, such that their sum equals zero.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0f9a288190b0ddfb673bd8e84b |
completed | April 18, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.