Triple
T5728864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonnie Wright |
E126332
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Bonnie Wright |
E126332
|
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: Bonnie Wright | Statement: [Bonnie Wright, name, Bonnie Wright]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bonnie Wright Context triple: [Bonnie Wright, name, Bonnie Wright]
-
A.
Bonnie Wright
chosen
Bonnie Wright is an English actress and filmmaker best known for playing Ginny Weasley in the Harry Potter film series.
-
B.
Prunella Scales
Prunella Scales is an English actress best known for her comic role as Sybil Fawlty in the classic British sitcom "Fawlty Towers."
-
C.
Hermione Baddeley
Hermione Baddeley was an English character actress known for her sharp-tongued, memorable supporting roles in British cinema and later in Hollywood films and television.
-
D.
Evanna Lynch
Evanna Lynch is an Irish actress best known for playing Luna Lovegood in the Harry Potter film series.
-
E.
Jane Wenham
Jane Wenham was a British actress known for her work in mid-20th-century film, television, and theatre.
- 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_69c0082f723881908ce8bb13a0c0f8b7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0250d5f4c8190a36b43ef5e6c7837 |
completed | March 22, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a8a1d08819080f071eb22db54d3 |
completed | March 22, 2026, 9:09 p.m. |
Created at: March 22, 2026, 3:47 p.m.