Triple
T22230023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dianna De La Garza |
E549441
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Dianna |
—
|
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: Dianna | Statement: [Dianna De La Garza, givenName, Dianna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dianna Context triple: [Dianna De La Garza, givenName, Dianna]
-
A.
Diane
Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
-
B.
Dianne
chosen
Dianne is a feminine given name commonly used in English-speaking countries, often associated with the Roman goddess Diana and borne by various notable figures.
-
C.
Diana
Diana is a renowned sculpture by Brazilian-Italian modernist artist Victor Brecheret, exemplifying his stylized, classical approach to the human figure.
-
D.
Diana
Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
-
E.
Deanna
Deanna is a feminine given name commonly used in English-speaking countries.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf173308190a3d21bfc59b39728 |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.