Triple
T21490615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Da Vinci's Demons |
E530225
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Laura Haddock |
—
|
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: Laura Haddock | Statement: [Da Vinci's Demons, starredActor, Laura Haddock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Haddock Context triple: [Da Vinci's Demons, starredActor, Laura Haddock]
-
A.
Laura Haddock
chosen
Laura Haddock is an English actress known for her roles in films like "Guardians of the Galaxy" and various British television series.
-
B.
Lorna Adams
Lorna Adams is best known as the wife of legendary American comedian and television pioneer Milton Berle.
-
C.
Beth Dawes
Beth Dawes is a married suburban woman in the television series "Mad Men" who becomes romantically involved with advertising executive Pete Campbell.
-
D.
Rebecca Harris
Rebecca Harris is a fictional character portrayed by Jennifer Carpenter, best known as the determined FBI agent in the television series "Limitless."
-
E.
Rebecca Harris
Rebecca Harris is an actress known for her role in the television series "Outsiders."
- 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea3aee648190ba845f0c7d8110dd |
completed | April 23, 2026, 9:45 a.m. |
Created at: April 16, 2026, 6:22 p.m.