Triple
T21858215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yenisei inscriptions |
E539688
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | corpus of inscriptions |
C9642
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: corpus of inscriptions Context triple: [Yenisei inscriptions, instanceOf, corpus of inscriptions]
-
A.
inscription corpus
chosen
An inscription corpus is a systematically collected and organized body of inscribed texts (such as carvings on stone, metal, or other durable materials) used for linguistic, historical, and archaeological analysis.
-
B.
ancient inscriptions
Ancient inscriptions are texts or symbols carved, engraved, or written on durable materials such as stone, metal, or clay by past civilizations, serving as primary evidence of their language, culture, beliefs, and historical events.
-
C.
religious inscription
A religious inscription is a text carved, written, or otherwise permanently recorded on a durable surface that conveys sacred messages, prayers, dedications, or doctrinal statements associated with a particular faith tradition.
-
D.
multilingual inscription
A multilingual inscription is a written text or engraving that presents the same or related content in two or more languages, often to communicate across linguistic groups or preserve information for diverse audiences.
-
E.
epigraphic text
An epigraphic text is an inscription carved, engraved, or otherwise permanently marked on a durable material, studied for its historical, linguistic, and cultural information.
- F. None of above.
Provenance (1 batch)
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_69e0c47829648190bbe2d1d7033768ec |
completed | April 16, 2026, 11:14 a.m. |
Created at: April 16, 2026, 6:56 p.m.