Triple
T10025470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reitia |
E200712
|
entity |
| Predicate | epigraphicEvidenceLanguage |
P15804
|
FINISHED |
| Object | Venetic language |
—
|
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: Venetic language | Statement: [Reitia, epigraphicEvidenceLanguage, Venetic language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: epigraphicEvidenceLanguage Context triple: [Reitia, epigraphicEvidenceLanguage, Venetic language]
-
A.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
B.
epigraphicType
Indicates the specific kind or category of an inscription as classified in epigraphic studies.
-
C.
secondaryLanguageOfInscriptions
Indicates that a specified language serves as the secondary language used in the inscriptions associated with a given entity.
-
D.
ancientLanguages
Indicates that the related entities are languages that originated in and were used during ancient historical periods.
-
E.
officialLanguageOfInscriptions
Indicates the language officially used in the inscriptions associated with a particular entity.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcde2009081908eddda7813617df4 |
completed | April 2, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:53 p.m.