Triple
T7828989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gianna Bryant |
E181317
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gianna |
E187345
|
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: Gianna | Statement: [Gianna Bryant, givenName, Gianna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gianna Context triple: [Gianna Bryant, givenName, Gianna]
-
A.
Gianna
chosen
Gianna is a feminine given name of Italian origin, often associated with the late Gianna Bryant, daughter of basketball legend Kobe Bryant.
-
B.
Gina
Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
-
C.
Gianna Fregonara
Gianna Fregonara is an Italian journalist known for her work in national media and her marriage to politician Enrico Letta.
-
D.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
E.
Jenna
Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb04aaed1881908e1da129a43ef9c7 |
completed | March 30, 2026, 11:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14b955488190a4ce0178d84d1dc6 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 4:44 p.m.