Triple
T17128963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramon Casas |
E415672
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Café |
E797453
|
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: The Café | Statement: [Ramon Casas, notableWork, The Café]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Café Context triple: [Ramon Casas, notableWork, The Café]
-
A.
The Cafe
The Cafe is a casual dining spot where people can relax, socialize, and enjoy beverages and light meals.
-
B.
Le Café
Le Café is a satirical verse dialogue by French poet Jean-Baptiste Rousseau that critiques contemporary society and literary culture through a conversation set in a coffeehouse.
-
C.
The Café Scene
chosen
The Café Scene is a painting by French artist Henri Gervex that vividly captures the lively social atmosphere of a Parisian café in the late 19th century.
-
D.
Carnation Café
Carnation Café is a classic table-service restaurant in Disneyland known for its nostalgic Main Street ambiance and traditional American comfort food.
-
E.
At the Café
"At the Café" is a political dialogue by Italian anarchist Errico Malatesta that explores and explains anarchist ideas through conversations in a café setting.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f0291ee881908fb10a8ccd7faa41 |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01414a51d4819086c2346fe2d4fce4 |
completed | May 11, 2026, 2:39 a.m. |
Created at: April 10, 2026, 5:36 a.m.