Triple
T18637046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman province of Lazicum |
E455577
|
entity |
| Predicate | romanizationLevel |
P132487
|
FINISHED |
| Object | partially romanized frontier region |
—
|
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: partially romanized frontier region | Statement: [Roman province of Lazicum, romanizationLevel, partially romanized frontier region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanizationLevel Context triple: [Roman province of Lazicum, romanizationLevel, partially romanized frontier region]
-
A.
romanizationType
Indicates the specific system or method used to convert text from one writing system into its Roman (Latin) alphabet representation.
-
B.
romanizationOfToponymType
Indicates a relationship where a specific type of place-name is expressed in a romanized (Latin-script) form corresponding to its original writing system.
-
C.
romanizationFrom
Indicates that one entity is a romanized representation derived from the script or writing system of another entity.
-
D.
hasRomanizationStandard
Indicates that an entity’s romanized form follows a specified romanization standard or system.
-
E.
romanizationContext
Indicates the specific system, rules, or circumstances under which a script or language is converted into its romanized form.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc9fa6c81909e1b988bdfb5ebcc |
completed | April 19, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69e478d4a7948190a4bb9223bb5dddfc |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e485f5d1588190b44f31cbc54c0a9d |
completed | April 19, 2026, 7:36 a.m. |
Created at: April 10, 2026, 11:46 a.m.