Triple
T11813682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romania and Moldova |
E280940
|
entity |
| Predicate | shareLatinScriptUsage |
P16462
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Romania and Moldova, shareLatinScriptUsage, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareLatinScriptUsage Context triple: [Romania and Moldova, shareLatinScriptUsage, yes]
-
A.
hasLatinInfluence
Indicates that one entity exerts or reflects cultural, linguistic, or stylistic influence derived from Latin on another entity.
-
B.
usesLatinAlphabetSince
Indicates that an entity has employed the Latin alphabet as its writing system starting from a specific point in time and continuing thereafter.
-
C.
associatedLanguageScript
chosen
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
D.
frequencyInLatinAmerica
Indicates how often something occurs or is present within Latin America.
-
E.
spanishVersionUsage
Indicates how and in what context the Spanish-language version of something is used.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a658f918819092c2db05fe2ab0ce |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a24e9a088190aff7932d1ff93dbf |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.