Triple
T22355698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lara Worthington |
E552646
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | 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: Bingle | Statement: [Lara Worthington, familyName, Bingle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bingle Context triple: [Lara Worthington, familyName, Bingle]
-
A.
Bingle
chosen
Bingle is the surname of Australian media personality and former model Lara Bingle.
-
B.
Groudle
Groudle is a small coastal settlement on the Isle of Man, known for its scenic bay and the historic Groudle Glen Railway.
-
C.
Binky
Binky is a fictional character from the children's animated series "Arthur," known as a tough-looking but kind-hearted bulldog who plays the clarinet.
-
D.
Binnie
Binnie is the surname of Brian Binnie, a Scottish-American test pilot and astronaut known for flying SpaceShipOne on its historic suborbital spaceflights.
-
E.
Briggy
Briggy is a familiar or affectionate nickname derived from the given name Brigham.
- 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.