Triple
T16268176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nato Vachnadze |
E394926
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Vachnadze |
E394926
|
NE 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: Vachnadze | Statement: [Nato Vachnadze, familyName, Vachnadze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vachnadze Context triple: [Nato Vachnadze, familyName, Vachnadze]
-
A.
Vachnadze
chosen
Vachnadze is a Georgian noble family name historically associated with prominent figures in Georgian culture and society.
-
B.
Tavaeli
Tavaeli is a regional dialect of the Kaili language spoken by communities in Central Sulawesi, Indonesia.
-
C.
Tsakhuri
Tsakhuri is an alternative name for the Tsakhur language, a Northeast Caucasian language spoken primarily in parts of Azerbaijan and Dagestan.
-
D.
Chkhaveri
Chkhaveri is a traditional Georgian grape variety known for producing distinctive, often semi-sweet rosé and red wines, particularly in western Georgia.
-
E.
Shekvetili
Shekvetili is a coastal village and resort area on Georgia’s Black Sea shore, known for its beaches, pine forests, and cultural attractions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245ca5c708190a1e98ab37740c032 |
completed | April 17, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017bb1d64819080f007656307f58b |
completed | May 10, 2026, 5:29 a.m. |
Created at: April 10, 2026, 5:05 a.m.