Triple
T13402704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Jamieson |
E319871
|
entity |
| Predicate | worksIn |
P1527
|
FINISHED |
| Object | Beaumont-sur-Mer |
E1029193
|
NE FINISHED |
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: Beaumont-sur-Mer | Statement: [Lawrence Jamieson, worksIn, Beaumont-sur-Mer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaumont-sur-Mer Context triple: [Lawrence Jamieson, worksIn, Beaumont-sur-Mer]
-
A.
Beaumont-sur-Mer
chosen
Beaumont-sur-Mer is a fictional upscale seaside town that serves as the primary setting for the film "Bedtime Story."
-
B.
Saint-Laurent-sur-Mer
Saint-Laurent-sur-Mer is a coastal commune in Normandy, France, historically significant for its location at the heart of the D-Day landings during World War II.
-
C.
Hautot-sur-Mer
Hautot-sur-Mer is a coastal commune in northern France, near Dieppe, known for its World War II history and military cemetery commemorating Canadian soldiers.
-
D.
Cayeux-sur-Mer
Cayeux-sur-Mer is a coastal commune in northern France known for its long pebble beach and traditional wooden beach huts along the English Channel.
-
E.
Dives-sur-Mer
Dives-sur-Mer is a coastal commune in northwestern France, known for its historic harbor linked to William the Conqueror’s 1066 expedition to England.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4982e0819087a9fcb2fa88541f |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b058bc688190b3549d1cac6f4576 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 9:34 p.m.