Triple
T1854946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mkhedruli |
E41679
|
entity |
| Predicate | hasDistinctNumeralsHistorically |
P33609
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mkhedruli, hasDistinctNumeralsHistorically, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctNumeralsHistorically Context triple: [Mkhedruli, hasDistinctNumeralsHistorically, yes]
-
A.
historicallyConsidered
Indicates that one entity has been regarded or classified in a particular way relative to another entity during a past historical period.
-
B.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
-
C.
hasHistoricalSignificance
Indicates that something possesses notable importance or influence within a historical context or period.
-
D.
historicallySpoke
Indicates that an entity used a particular language as a spoken language during some period in the past.
-
E.
historicallyRecognizedAs
Indicates that an entity has been acknowledged or designated under a particular name, status, or role during a past historical period.
- 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb231de14819091da3a20ed03c430 |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafde4598819099d8229128348fd3 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb22f36f08190abf5e295ddf310d7 |
completed | March 7, 2026, 5:05 a.m. |
Created at: March 4, 2026, 7:33 p.m.