Triple
T11037223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgiana Darcy |
E260917
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Georgiana |
E326337
|
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: Georgiana | Statement: [Georgiana Darcy, givenName, Georgiana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgiana Context triple: [Georgiana Darcy, givenName, Georgiana]
-
A.
Georgiana
chosen
Georgiana is a feminine given name of Greek origin, often associated with elegance and historically borne by various notable women in British and European society.
-
B.
Georgiana Drew
Georgiana Drew was a 19th-century American stage actress and member of the prominent Barrymore theatrical family.
-
C.
Georgina
Georgina is a lakeside town in Ontario, Canada, known for its recreational waterfront communities and proximity to Lake Simcoe.
-
D.
Georgina
Georgina is a feminine given name used in various English-speaking and European countries, often considered a variant of Georgia or the feminine form of George.
-
E.
Letitia
Letitia is a feminine given name of Latin origin, commonly associated with the meaning "joy" or "happiness."
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797fd5fe081908af13835b18de7b8 |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a9c669608190af97c461beaf9f31 |
completed | April 18, 2026, 3:56 p.m. |
Created at: April 8, 2026, 9:25 p.m.