Triple
T18131673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Lucas |
E434027
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jessica Lucas |
—
|
NE NERFINISHED |
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: Jessica Lucas | Statement: [Jessica Lucas, name, Jessica Lucas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jessica Lucas Context triple: [Jessica Lucas, name, Jessica Lucas]
-
A.
Jessica Lucas
chosen
Jessica Lucas is a Canadian actress known for her roles in film and television, including prominent appearances in projects like the monster movie "Cloverfield."
-
B.
Kyliegh Curran
Kyliegh Curran is an American actress best known for her roles in the horror film "Doctor Sleep" and the Netflix series "The Fall of the House of Usher."
-
C.
Lilly McDowell
Lilly McDowell is an American actress known for roles in film and television and as the daughter of actors Mary Steenburgen and Malcolm McDowell.
-
D.
Lilly McDowell
Lilly McDowell is an American actress known for her work in film and television and as the daughter of actors Ted Danson and Mary Steenburgen.
-
E.
Taylor Russell
Taylor Russell is a Canadian actress best known for her breakout role in the Netflix sci-fi series "Lost in Space" and acclaimed performances in films such as "Waves" and "Bones and All."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddf2c68881909dfbe59df15ddccc |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.