Triple
T7163109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cynthia Nixon |
E166995
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Cynthia Nixon |
E166995
|
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: Cynthia Nixon | Statement: [Cynthia Nixon, name, Cynthia Nixon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cynthia Nixon Context triple: [Cynthia Nixon, name, Cynthia Nixon]
-
A.
Cynthia Nixon
chosen
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.
-
B.
Kim Cattrall
Kim Cattrall is a British-Canadian actress best known for her role as Samantha Jones in the television series "Sex and the City."
-
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.
Anne McDonnell
Anne McDonnell was an American socialite best known as the first wife of industrialist Henry Ford II.
-
E.
Debra Messing
Debra Messing is an American actress best known for her Emmy-winning role as Grace Adler on the sitcom "Will & Grace."
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82feee481908fa180ea8c9924fa |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adc8b06c81909791e38becb594f6 |
completed | March 28, 2026, 10:30 a.m. |
Created at: March 27, 2026, 2:47 p.m.