Triple
T21744023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah MacKenzie |
E536737
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Catherine Bell |
—
|
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: Catherine Bell | Statement: [Sarah MacKenzie, portrayedBy, Catherine Bell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Catherine Bell Context triple: [Sarah MacKenzie, portrayedBy, Catherine Bell]
-
A.
Catherine Bell
Catherine Bell is a British former Olympic rower who competed for Great Britain in the 1990s.
-
B.
Catherine Bell
chosen
Catherine Bell is an American actress best known for her role as Lieutenant Colonel Sarah "Mac" MacKenzie on the television series JAG.
-
C.
Samantha Beckinsale
Samantha Beckinsale is a British actress known for her work in television dramas and comedies, and as the half-sister of actress Kate Beckinsale.
-
D.
Kristin Scott Thomas
Kristin Scott Thomas is an acclaimed British actress known for her nuanced performances in films such as "The English Patient," "Four Weddings and a Funeral," and "The Horse Whisperer."
-
E.
Julia Ormond
Julia Ormond is a British actress known for her roles in films such as "Legends of the Fall," "Sabrina," and "The Curious Case of Benjamin Button."
- 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a74592c8190959af631d72df479 |
completed | April 28, 2026, 2:24 a.m. |
Created at: April 16, 2026, 6:49 p.m.