Triple
T22355708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lara Worthington |
E552646
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Being Lara Bingle |
—
|
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: Being Lara Bingle | Statement: [Lara Worthington, notableWork, Being Lara Bingle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Being Lara Bingle Context triple: [Lara Worthington, notableWork, Being Lara Bingle]
-
A.
Lara Bingle
chosen
Lara Bingle is an Australian model, media personality, and entrepreneur best known for her high-profile advertising campaigns and reality television appearances.
-
B.
Cilla
Cilla is a character in Toni Morrison’s opera "Margaret Garner," which dramatizes the true story of an enslaved woman’s desperate bid for freedom in pre–Civil War America.
-
C.
Cilla
Cilla is a feminine given name, commonly used as a diminutive form of Priscilla.
-
D.
Alison Sutcliffe
Alison Sutcliffe is a British theatre director known for her work with major UK companies and for her former marriage to actor Sir Ben Kingsley.
-
E.
Liza Tarbuck
Liza Tarbuck is an English actress, television and radio presenter known for her work across British entertainment, including hosting popular quiz and variety shows.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157cf94508190b0f2c63ddfecb813 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:44 p.m.