Triple
T16937835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ella Henderson |
E410875
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gabriella |
E307088
|
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: Gabriella | Statement: [Ella Henderson, givenName, Gabriella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabriella Context triple: [Ella Henderson, givenName, Gabriella]
-
A.
Gabriella
chosen
Gabriella is a feminine given name of Italian origin, commonly used in many languages and often associated with the meaning "God is my strength."
-
B.
Gabrielle
Gabrielle is the birth name of the iconic French fashion designer Coco Chanel, founder of the Chanel brand.
-
C.
Gabrielle
"Gabrielle" is a popular Swedish-language song by the Hootenanny Singers, known for its melodic folk-pop style and enduring appeal in Scandinavian music.
-
D.
Gabrielle
Gabrielle is a feminine given name of Hebrew origin meaning "God is my strength," used in various cultures and languages.
-
E.
Gabrielle
Gabrielle is a character in the film "Midnight in Paris," portrayed as a charming antiques dealer who becomes Gil Pender’s romantic partner by the story’s end.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf2b88bc8190aeb7b07032478ae3 |
completed | April 18, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfe5210c8190873be6ccf2369b34 |
completed | May 10, 2026, 6:35 p.m. |
Created at: April 10, 2026, 5:30 a.m.