Triple
T21687000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Overboard (2018 film) |
E535254
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Michael Barrett |
—
|
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: Michael Barrett | Statement: [Overboard (2018 film), cinematographyBy, Michael Barrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Barrett Context triple: [Overboard (2018 film), cinematographyBy, Michael Barrett]
-
A.
Michael Barrett
Michael Barrett is a creator known for developing the work titled "The Choice."
-
B.
Michael Barrett
chosen
Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
-
C.
Matthew Barrett
Matthew Barrett is an Irish cardiologist best known as the long-term partner of former Taoiseach and current Tánaiste Leo Varadkar.
-
D.
Ron Barrett
Ron Barrett is an American illustrator best known for his whimsical artwork in the classic children's book "Cloudy with a Chance of Meatballs."
-
E.
Craig Barrett
Craig Barrett is an American business executive and engineer best known for serving as CEO and chairman of Intel Corporation.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cc31b8819086ca980521f94501 |
completed | April 27, 2026, 5:03 p.m. |
Created at: April 16, 2026, 6:44 p.m.