Triple
T15389304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Very Good Girls |
E367996
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Kiernan Shipka |
E895947
|
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: Kiernan Shipka | Statement: [Very Good Girls, castMember, Kiernan Shipka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiernan Shipka Context triple: [Very Good Girls, castMember, Kiernan Shipka]
-
A.
Kiernan Shipka
chosen
Kiernan Shipka is an American actress best known for her leading roles in the series Mad Men and Chilling Adventures of Sabrina.
-
B.
Rhiannon Weaver
Rhiannon Weaver is a central figure in Kingsley Amis’s novel *The Old Devils*, around whom much of the book’s interpersonal drama and emotional tension revolves.
-
C.
Anna Torv
Anna Torv is an Australian actress best known for her lead role as FBI agent Olivia Dunham in the science fiction television series "Fringe."
-
D.
Elisha Cuthbert
Elisha Cuthbert is a Canadian actress known for her roles in film and television, including prominent parts in series like "24" and various comedy and thriller movies.
-
E.
Brianne Tju
Brianne Tju is an American actress known for her roles in teen and horror television series and films, including the thriller "47 Meters Down: Uncaged."
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e761b688190893a81246b735b76 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa92e5f5c81908f54e91b7f16607e |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 3:19 a.m.