Triple
T2587350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patricia |
E58034
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Patricia Clarkson |
E298767
|
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: Patricia Clarkson | Statement: [Patricia, hasNotableBearer, Patricia Clarkson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patricia Clarkson Context triple: [Patricia, hasNotableBearer, Patricia Clarkson]
-
A.
Patricia Clarkson
chosen
Patricia Clarkson is an American actress acclaimed for her versatile performances in film, television, and theater, often in complex supporting roles.
-
B.
Anneke Wills
Anneke Wills is a British actress best known for playing the companion Polly in the classic science fiction television series Doctor Who during the 1960s.
-
C.
Lesley Garrett
Lesley Garrett is an English soprano and media personality known for her operatic performances and popular classical crossover work.
-
D.
Edith Lesley
Edith Lesley was an American educator and founder of the teacher-training institution that evolved into Lesley University in Cambridge, Massachusetts.
-
E.
Sheila Hancock
Sheila Hancock is a British actress and author renowned for her extensive work in theatre, television, and film, as well as her appearances as a television presenter and panelist.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd3f8a3888190889c537e6df07305 |
completed | March 7, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01d2bfe788190b629ccbf96f8d98d |
completed | March 10, 2026, 1:31 p.m. |
Created at: March 6, 2026, 9:49 p.m.