Triple
T16480176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Historical Monuments of Mtskheta |
E400292
|
entity |
| Predicate | officialNameInLocalLanguage |
P86937
|
FINISHED |
| Object | მცხეთის ისტორიული ძეგლები |
—
|
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: მცხეთის ისტორიული ძეგლები | Statement: [Historical Monuments of Mtskheta, officialNameInLocalLanguage, მცხეთის ისტორიული ძეგლები]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialNameInLocalLanguage Context triple: [Historical Monuments of Mtskheta, officialNameInLocalLanguage, მცხეთის ისტორიული ძეგლები]
-
A.
officialNameLocal
chosen
Indicates the officially recognized name of an entity as used in the local or native language context.
-
B.
institutionNativeName
Indicates that an institution is associated with its official or commonly used name in the institution’s original or local language.
-
C.
translationOfOfficialName
Indicates that one name is an official translation of another name in a different language.
-
D.
officialNameInSpanish
Indicates the officially recognized name of an entity when expressed in the Spanish language.
-
E.
officialName
Indicates the formally recognized name assigned to an entity by an authoritative body or source.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e01f6c88190b75a0d6c94786426 |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:13 a.m.