Triple
T9579020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kick-Ass 2 |
E231120
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Lindy Booth |
E264893
|
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: Lindy Booth | Statement: [Kick-Ass 2, starring, Lindy Booth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lindy Booth Context triple: [Kick-Ass 2, starring, Lindy Booth]
-
A.
Lindy Booth
chosen
Lindy Booth is a Canadian actress known for her roles in television series and films, particularly in genre and adventure projects.
-
B.
Karin Booth
Karin Booth was an American film and television actress active in the 1940s and 1950s, known for her roles in dramas, westerns, and adventure films.
-
C.
Hilary Booth
Hilary Booth is a flamboyant, temperamental leading lady and radio actress on the 1940s-set television series "Remember WENN."
-
D.
Laura Bickford
Laura Bickford is an American film producer best known for her work on acclaimed independent and studio films, including the Oscar-winning drama "Traffic."
-
E.
Lisa Baird
Lisa Baird is an American sports executive who served as commissioner of the National Women's Soccer League (NWSL).
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99aece1081908287e03106de020f |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eab0860c819091b0169f82eac47f |
completed | April 5, 2026, 4:53 a.m. |
Created at: March 30, 2026, 8:05 p.m.