Triple
T8362471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caesonia |
E197041
|
entity |
| Predicate | partOfRomanNamingSystem |
P82301
|
FINISHED |
| Object | tria nomina |
—
|
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: tria nomina | Statement: [Caesonia, partOfRomanNamingSystem, tria nomina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfRomanNamingSystem Context triple: [Caesonia, partOfRomanNamingSystem, tria nomina]
-
A.
romanNomen
Indicates that an entity has a specific Roman nomen, i.e., the clan or gens name within the traditional Roman naming system.
-
B.
royalPrenomen
Indicates the formal throne name adopted by a monarch as part of their royal titulary.
-
C.
isPraenomenOf
Indicates that a given personal name functions as the praenomen (given name) of a specific individual.
-
D.
hasRomanName
Indicates that an entity is associated with or known by a name derived from or used in ancient Rome.
-
E.
preRomanName
Indicates the name by which an entity (such as a place or people) was known before the Roman period or prior to receiving a Roman-era name.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8074e4588190b394d1622adca2cb |
completed | March 31, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69cb70ca25548190b0f90c5384e3fb3c |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 6 p.m.