Triple
T1705679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linear B inscriptions |
E36867
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | inscription corpus |
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: inscription corpus Context triple: [Linear B inscriptions, instanceOf, inscription corpus]
-
A.
epigrapher
An epigrapher is a specialist who studies, deciphers, and interprets inscriptions or writings engraved on durable materials such as stone, metal, or pottery to understand historical languages and cultures.
-
B.
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.
-
C.
ancient manuscripts
Ancient manuscripts are original handwritten documents from past civilizations, typically preserved on materials like papyrus, parchment, or early paper, that provide primary evidence of historical, religious, literary, or scientific thought.
-
D.
documentation corpus
A documentation corpus is a structured collection of written materials, such as manuals, guides, and reference texts, compiled to provide comprehensive information and support for a specific domain, product, or system.
-
E.
Etruscan inscription
An Etruscan inscription is a text written in the ancient Etruscan language, typically carved or painted on durable materials such as stone, metal, or pottery, providing evidence of the culture, religion, and daily life of the Etruscan civilization.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
Created at: March 4, 2026, 7:30 p.m.