Triple
T6518934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rossi |
E148330
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Rossa |
E521486
|
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: Rossa | Statement: [Rossi, hasVariant, Rossa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rossa Context triple: [Rossi, hasVariant, Rossa]
-
A.
Rossa
chosen
Rossa is an alternative name for Hürrem Sultan, the influential 16th-century wife of Ottoman Sultan Suleiman the Magnificent and a powerful political figure in the empire.
-
B.
Rosse
Rosse is an alternative spelling or variant form of the name Ross, which is used as both a given name and a surname.
-
C.
Rosa
Rosa is the birth name of Linda Christian, a Mexican film actress known as the first "Bond girl" for her role in the 1954 television adaptation of Casino Royale.
-
D.
Rosa
Rosa is a celebrated poem by Nikki Giovanni that honors civil rights icon Rosa Parks and reflects on the broader struggle for racial justice.
-
E.
Rosa
Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
- 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_69c687e68e748190baceb9298f32d3ed |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ac11d0e481908103c4b51de9521e |
completed | March 27, 2026, 4:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d51af5308190928c97ceb5d5fa2d |
completed | March 27, 2026, 7:06 p.m. |
Created at: March 27, 2026, 1:44 p.m.