Triple
T10513703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvia Syms |
E247978
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Beatie Edney |
E416541
|
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: Beatie Edney | Statement: [Sylvia Syms, child, Beatie Edney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beatie Edney Context triple: [Sylvia Syms, child, Beatie Edney]
-
A.
Beatie Edney
chosen
Beatie Edney is a British actress best known for her role as Heather MacLeod in the film "Highlander" and its sequel, as well as for numerous appearances in British television dramas.
-
B.
Belinda Beatty
Belinda Beatty is known as the wife of the late American character actor Ned Beatty.
-
C.
Elaine Baylor
Elaine Baylor is known as the wife of legendary Basketball Hall of Famer Elgin Baylor.
-
D.
Lisa Blount
Lisa Blount was an American actress and producer best known for her acclaimed supporting role in the film "An Officer and a Gentleman."
-
E.
Anita Morris
Anita Morris was an American actress, singer, and dancer known for her sultry screen presence and scene-stealing roles in film, television, and on Broadway.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509cade0c81908fcbd54a90106bf9 |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b13f4fc8190863d6e1aa7da5733 |
completed | April 10, 2026, 7:10 p.m. |
Created at: April 6, 2026, 12:27 p.m.