Triple
T6457064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex and the City |
E142019
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Kim Cattrall |
E136503
|
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: Kim Cattrall | Statement: [Sex and the City, portrayedBy, Kim Cattrall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Cattrall Context triple: [Sex and the City, portrayedBy, Kim Cattrall]
-
A.
Kim Cattrall
chosen
Kim Cattrall is a British-Canadian actress best known for her role as Samantha Jones in the television series "Sex and the City."
-
B.
Cynthia Nixon
Cynthia Nixon is an American actress and activist best known for her role as Miranda Hobbes in the television series "Sex and the City" and its related films.
-
C.
Elizabeth Berridge
Elizabeth Berridge is an American actress best known for her role as Constanze Mozart in the Academy Award–winning film "Amadeus."
-
D.
Annabella Sciorra
Annabella Sciorra is an American actress known for her work in film and television, including acclaimed roles in movies like "Jungle Fever" and the TV series "The Sopranos."
-
E.
Michelle Pfeiffer
Michelle Pfeiffer is an acclaimed American actress known for her versatile performances in films such as "Scarface," "The Fabulous Baker Boys," and "Batman Returns."
- 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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d639ec8190bb0a806da4118440 |
completed | March 22, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bdef4a881908f3d7b6eefab7def |
completed | March 27, 2026, 9:20 a.m. |
Created at: March 22, 2026, 4:48 p.m.