Triple
T1846897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asomtavruli |
E41302
|
entity |
| Predicate | contemporaryUse |
P34114
|
FINISHED |
| Object | ceremonial inscriptions |
—
|
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: ceremonial inscriptions | Statement: [Asomtavruli, contemporaryUse, ceremonial inscriptions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contemporaryUse Context triple: [Asomtavruli, contemporaryUse, ceremonial inscriptions]
-
A.
contemporary
Indicates that two entities exist, occur, or are active during the same time period or historical era.
-
B.
modernUse
Indicates how something is currently used or applied in modern times.
-
C.
contemporaryReception
Indicates how a work, event, or figure was received, perceived, or evaluated by audiences and critics at the time it originally appeared or occurred.
-
D.
contemporaryWith
Indicates that two entities existed, occurred, or were active during the same time period.
-
E.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
- 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdca6d8819083c66f3a29fd9fd1 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb32a8d548190a231c7c2ce276a5e |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:33 p.m.