Triple
T17667925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Hampshire |
E440435
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Susan Hampshire |
E440435
|
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: Susan Hampshire | Statement: [Susan Hampshire, name, Susan Hampshire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susan Hampshire Context triple: [Susan Hampshire, name, Susan Hampshire]
-
A.
Susan Hampshire
chosen
Susan Hampshire is an English actress best known for her award-winning performances in British television dramas and period adaptations.
-
B.
Patricia Routledge
Patricia Routledge is an English actress and comedian best known for her acclaimed stage work and for starring as the snobbish Hyacinth Bucket in the sitcom "Keeping Up Appearances."
-
C.
Lesley Garrett
Lesley Garrett is an English soprano and media personality known for her operatic performances and popular classical crossover work.
-
D.
Helen Mary Warnock
Helen Mary Warnock was a prominent British philosopher and educationalist best known for her influential work on ethics, special education, and public policy.
-
E.
Frances Barber
Frances Barber is an English actress known for her extensive work in film, television, and theatre, including roles in productions such as "Film Stars Don’t Die in Liverpool."
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46eaaaec8819086977d8a5210c44e |
completed | April 19, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0242e7b48481908af4b941018c030e |
completed | May 11, 2026, 8:58 p.m. |
Created at: April 10, 2026, 9:58 a.m.