Triple
T19305927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlene Francis |
E482827
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Arline |
—
|
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: Arline | Statement: [Arlene Francis, givenName, Arline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arline Context triple: [Arlene Francis, givenName, Arline]
-
A.
Arline
chosen
Arline is a feminine given name, often used in English-speaking countries and associated with several notable women in the arts and entertainment.
-
B.
Earline
Earline is a character in Ishmael Reed's satirical novel "Mumbo Jumbo," which explores themes of African American culture, history, and resistance.
-
C.
Harline
Harline is a surname most notably associated with Leigh Harline, an American film composer known for his work with Walt Disney Studios.
-
D.
Arletta
Arletta is a feminine given name of likely European origin, used for personal naming.
-
E.
Arletta
Arletta, better known as Herleva of Falaise, was the mother of William the Conqueror and a notable figure in 11th-century Norman history.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604c84fe08190869463bdd0324160 |
completed | April 20, 2026, 10:49 a.m. |
Created at: April 10, 2026, 1:31 p.m.