Triple
T22867666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego Spirit |
E567097
|
entity |
| Predicate | notablePlayer |
P304
|
FINISHED |
| Object | Daniela |
—
|
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: Daniela | Statement: [San Diego Spirit, notablePlayer, Daniela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniela Context triple: [San Diego Spirit, notablePlayer, Daniela]
-
A.
Daniela
Daniela is a feminine given name commonly used in many languages, often as the female form of Daniel.
-
B.
Romina
Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
-
C.
Alessandra
Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
-
D.
Alessandra
Alessandra is an Italian given name, the feminine form of Alessandro, equivalent to Alexandra in English.
-
E.
Corina
Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f0210b481908e0e6c4f95ba5a3b |
completed | April 29, 2026, 3:46 a.m. |
Created at: April 17, 2026, 3:38 p.m.