Triple
T23057179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carolina Crescentini |
E574190
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Carolina |
—
|
NE NERFINISHED |
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: Carolina | Statement: [Carolina Crescentini, givenName, Carolina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carolina Context triple: [Carolina Crescentini, givenName, Carolina]
-
A.
Carolina
Carolina is a major municipality in Puerto Rico, known for its urban character, commercial centers, and proximity to San Juan.
-
B.
Carolina
Carolina is a common nickname for the University of North Carolina at Chapel Hill, a major public research university known for its strong academics and athletic programs.
-
C.
Carolina
chosen
Carolina is a feminine given name of Latin origin, commonly used in various languages as a form of Caroline or Charles.
-
D.
Carolina
Carolina is a landmark 16th-century criminal code of the Holy Roman Empire, issued under Emperor Charles V and known for systematizing criminal law and procedure in German territories.
-
E.
Carolina
Carolina is a locality in the San Miguel Department of El Salvador, known as a small town in the eastern part of the country.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245ba7ae48190be606dbc54120e39 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18681bec48190a8226b3d89d19b9f |
completed | April 29, 2026, 4:18 a.m. |
Created at: April 17, 2026, 3:55 p.m.