Triple
T17848816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belfast |
E445736
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Laura Berwick |
—
|
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 Berwick | Statement: [Belfast, producer, Laura Berwick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Berwick Context triple: [Belfast, producer, Laura Berwick]
-
A.
Laura Berwick
chosen
Laura Berwick is a film producer best known for her work on Kenneth Branagh’s acclaimed 2021 drama "Belfast."
-
B.
Laura Merriman
Laura Merriman is known as the spouse of Dwight Merriman, the co-founder and former CEO of DoubleClick and co-founder of MongoDB.
-
C.
Emily Wilkinson
Emily Wilkinson is an American social media personality and former patient coordinator best known as the wife of NFL quarterback Baker Mayfield.
-
D.
Laura Garrety
Laura Garrety is a central character in the dark comedy film "Very Bad Things," around whom much of the movie’s escalating chaos and moral collapse revolves.
-
E.
Emily Williamson
Emily Williamson was a pioneering British conservationist who co-founded what became the Royal Society for the Protection of Birds, helping launch the modern bird protection movement.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffd7e2c81909a42cc7ab64e7db9 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.