Triple
T14534058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sabrina Le Beauf |
E340990
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sabrina Le Beauf |
E340990
|
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: Sabrina Le Beauf | Statement: [Sabrina Le Beauf, name, Sabrina Le Beauf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sabrina Le Beauf Context triple: [Sabrina Le Beauf, name, Sabrina Le Beauf]
-
A.
Sabrina Le Beauf
chosen
Sabrina Le Beauf is an American actress best known for playing Sondra Huxtable on the hit television sitcom "The Cosby Show."
-
B.
Sabrina Fair
Sabrina Fair is a romantic comedy play by Samuel Taylor that inspired the classic Audrey Hepburn film "Sabrina."
-
C.
Sabrina Bryan
Sabrina Bryan is an American singer, actress, and dancer best known for starring in Disney Channel’s "The Cheetah Girls" franchise.
-
D.
Sabrina Lloyd
Sabrina Lloyd is an American actress best known for her roles on the television series "Sports Night" and "Sliders."
-
E.
Sabrina Plisco
Sabrina Plisco is a film editor known for her work on major feature films, including the fantasy musical sequel "Disenchanted."
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea053f9bc8190901b9d321811d881 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a589d488190b4a192f33d11092d |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.