Triple
T15305904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Career Girls |
E365895
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Claire Skinner |
E611292
|
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: Claire Skinner | Statement: [Career Girls, hasCastMember, Claire Skinner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claire Skinner Context triple: [Career Girls, hasCastMember, Claire Skinner]
-
A.
Claire Skinner
chosen
Claire Skinner is an English actress best known for her work in film, television, and theatre, including her role in the British sitcom "Outnumbered."
-
B.
Claire Jennings
Claire Jennings is a British film producer known for her work on acclaimed independent and genre films, including the 2017 psychological thriller "Breathe."
-
C.
Claire Wright
Claire Wright is known as the wife of Tom Wright, a prominent British New Testament scholar and former Bishop of Durham.
-
D.
Claire Keim
Claire Keim is a French actress and singer known for her work in film, television, and music.
-
E.
Claire Dodd
Claire Dodd was an American film actress of the 1930s and 1940s, often cast as sophisticated or scheming society women in Hollywood productions.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ccef14c819099c5ebe962e7f867 |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00aade82788190a5f3cedbc22065c4 |
completed | May 10, 2026, 3:57 p.m. |
Created at: April 10, 2026, 3:16 a.m.