Triple
T3011697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | მტკვარი |
E82235
|
entity |
| Predicate | მნიშვნელობა |
P428
|
FINISHED |
| Object | ისტორიული მნიშვნელობა სამხრეთ კავკასიაში |
—
|
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: ისტორიული მნიშვნელობა სამხრეთ კავკასიაში | Statement: [მტკვარი, მნიშვნელობა, ისტორიული მნიშვნელობა სამხრეთ კავკასიაში]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: მნიშვნელობა Context triple: [მტკვარი, მნიშვნელობა, ისტორიული მნიშვნელობა სამხრეთ კავკასიაში]
-
A.
hasParticularSignificanceFor
Indicates that something holds a special, notable, or contextually important relevance or impact for a particular entity or situation.
-
B.
significance
chosen
Indicates that one entity holds particular importance, influence, or meaningful impact in relation to another entity or context.
-
C.
meaningComponent
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
D.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
E.
magnitude
Indicates a relationship where a quantitative size, extent, or intensity is assigned to or compared between entities or values.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a66c334819082d1d320c48eca1b |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad961a97188190809dc73430a8eda8 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.