Triple
T19505421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bright |
E488007
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Michael Tronick |
—
|
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 Tronick | Statement: [Bright, editedBy, Michael Tronick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Tronick Context triple: [Bright, editedBy, Michael Tronick]
-
A.
Michael Tronick
chosen
Michael Tronick is an American film editor known for his work on numerous major Hollywood productions across several decades.
-
B.
Lee M. E. Morin
Lee M. E. Morin is a U.S. Navy physician and NASA astronaut who flew aboard Space Shuttle Atlantis on the STS-110 mission to the International Space Station.
-
C.
Robert Klaus
Robert Klaus is a German economist and academic, known for his work in public finance and social policy and for being a member of the prominent von Weizsäcker family.
-
D.
Jerome Kagan
Jerome Kagan was an influential American psychologist and pioneer in developmental psychology, best known for his research on temperament in children and its impact on later behavior.
-
E.
Ann Belsky
Ann Belsky was a costume designer and the late wife of Canadian actor Rick Moranis.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635113fdc819098ea0f738d01925c |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.