Triple
T5752687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Women (2019 film) |
E126888
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Florence Pugh |
E8606
|
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: Florence Pugh | Statement: [Little Women (2019 film), stars, Florence Pugh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florence Pugh Context triple: [Little Women (2019 film), stars, Florence Pugh]
-
A.
Florence Pugh
chosen
Florence Pugh is an English actress acclaimed for her emotionally intense and versatile performances in films such as "Lady Macbeth," "Midsommar," and "Little Women."
-
B.
Lucy Boynton
Lucy Boynton is a British-American actress known for her roles in films such as "Bohemian Rhapsody" and "Sing Street," as well as various television dramas.
-
C.
Vanessa Kirby
Vanessa Kirby is an English actress known for her acclaimed performances in both film and television, including her breakout role as Princess Margaret in the Netflix series "The Crown."
-
D.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
-
E.
Tamsin Egerton
Tamsin Egerton is an English actress and model known for roles in films such as "St Trinian's," "Keeping Mum," and "The Look of Love."
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0288b580c81909e1289982b106695 |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e3e71988190a938a6d175023028 |
completed | March 22, 2026, 11:41 p.m. |
Created at: March 22, 2026, 3:48 p.m.