Triple
T9155045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Father Forgive |
E219687
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | religious inscription |
C25723
|
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: religious inscription Context triple: [Father Forgive, instanceOf, religious inscription]
-
A.
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.
-
B.
ancient Greek inscription
An ancient Greek inscription is a text carved, painted, or otherwise permanently marked on durable materials such as stone, metal, or pottery in the Greek language, typically serving public, religious, legal, or commemorative purposes in antiquity.
-
C.
Latin inscription
A Latin inscription is a text carved, engraved, or otherwise permanently marked in the Latin language on durable materials such as stone, metal, or pottery, typically serving commemorative, dedicatory, legal, or informational purposes.
-
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.
inscription corpus
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.
- F. None of above. chosen
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_69ca83e25418819093c6503deeaf30de |
completed | March 30, 2026, 2:08 p.m. |
Created at: March 30, 2026, 7:20 p.m.