Triple
T20497076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabella Figg |
E502902
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Arabella |
—
|
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: Arabella | Statement: [Arabella Figg, givenName, Arabella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arabella Context triple: [Arabella Figg, givenName, Arabella]
-
A.
Arabella
chosen
Arabella is a feminine given name of Latin origin, often associated with elegance and used in various English-speaking cultures.
-
B.
Arabella
Arabella is a romantic opera in three acts by Richard Strauss, first performed in 1933, known for its lush orchestration and exploration of love and social expectations in 19th-century Vienna.
-
C.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
D.
Cecilia
Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
-
E.
Cecilia
"Cecilia" is a popular, upbeat folk-rock song by the American duo Simon & Garfunkel, known for its catchy rhythm and playful lyrics.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbefe4c819098af5bfd4d92341d |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.