Triple
T15486880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Project Blue Book |
E377069
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object | Laura Mennell |
—
|
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 Mennell | Statement: [Project Blue Book, leadActor, Laura Mennell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Mennell Context triple: [Project Blue Book, leadActor, Laura Mennell]
-
A.
Laura Mennell
chosen
Laura Mennell is a Canadian actress known for her roles in science fiction and fantasy film and television, including appearances in projects like Watchmen and the series Alphas.
-
B.
Ann McMillan
Ann McMillan is the daughter of American physicist and Nobel laureate Edwin McMillan.
-
C.
Alison Mundy
Alison Mundy is the troubled, reluctant medium at the center of the British supernatural drama series "Afterlife," known for her intense encounters with the dead and emotional struggles with her gift.
-
D.
Laura Haddock
Laura Haddock is an English actress known for her roles in films like "Guardians of the Galaxy" and various British television series.
-
E.
Michelle Mylett
Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8f71a08190a440ff19dcc65312 |
completed | April 16, 2026, 1:46 a.m. |
Created at: April 10, 2026, 3:47 a.m.