Triple
T13721468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rina |
E329046
|
entity |
| Predicate | shortFor |
P43
|
FINISHED |
| Object | Catarina |
E64628
|
NE 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: Catarina | Statement: [Rina, shortFor, Catarina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Catarina Context triple: [Rina, shortFor, Catarina]
-
A.
Catharina
Catharina of Württemberg was a 19th-century German princess who became Queen consort of Westphalia through her marriage to Jérôme Bonaparte, Napoleon’s youngest brother.
-
B.
Catharina
Catharina is a feminine given name of Greek origin, commonly used in various European cultures and often associated with historical and religious figures.
-
C.
Caterina
chosen
Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
-
D.
Luisa
Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
-
E.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f3b46481909ceedfa78e9ca92b |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c20e45c8190968a5d88a2b3fe37 |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 9, 2026, 9:55 p.m.