Triple
T3129860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee and Cigarettes |
E65382
|
entity |
| Predicate | hasVignette |
P45542
|
FINISHED |
| Object |
Café au Lait
Café au Lait is one of the short, conversational vignettes in Jim Jarmusch’s film "Coffee and Cigarettes," featuring characters chatting over coffee in a minimalist, black-and-white setting.
|
E333326
|
NE FINISHED |
How this triple was built (4 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: Café au Lait | Statement: [Coffee and Cigarettes, hasVignette, Café au Lait]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Café au Lait Context triple: [Coffee and Cigarettes, hasVignette, Café au Lait]
-
A.
Cappachino
Cappachino is an alias of Cappadonna, an American rapper best known for his longtime affiliation with the Wu-Tang Clan.
-
B.
Latte Pronto
Latte Pronto is the central protagonist of the work "Fool's Paradise," around whom the story's main events and conflicts revolve.
-
C.
Coffee-Mate
Coffee-Mate is a popular non-dairy coffee creamer brand known for its wide variety of flavored and powdered creamers used to enhance coffee.
-
D.
Mocha
Mocha is a popular JavaScript test framework used primarily for running unit and integration tests in Node.js and browser-based applications.
-
E.
Mocha
Mocha is a subsidiary peak of the Carihuairazo volcanic massif in the Ecuadorian Andes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Café au Lait Triple: [Coffee and Cigarettes, hasVignette, Café au Lait]
Generated description
Café au Lait is one of the short, conversational vignettes in Jim Jarmusch’s film "Coffee and Cigarettes," featuring characters chatting over coffee in a minimalist, black-and-white setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Café au Lait Target entity description: Café au Lait is one of the short, conversational vignettes in Jim Jarmusch’s film "Coffee and Cigarettes," featuring characters chatting over coffee in a minimalist, black-and-white setting.
-
A.
Cappachino
Cappachino is an alias of Cappadonna, an American rapper best known for his longtime affiliation with the Wu-Tang Clan.
-
B.
Latte Pronto
Latte Pronto is the central protagonist of the work "Fool's Paradise," around whom the story's main events and conflicts revolve.
-
C.
Coffee-Mate
Coffee-Mate is a popular non-dairy coffee creamer brand known for its wide variety of flavored and powdered creamers used to enhance coffee.
-
D.
Mocha
Mocha is a popular JavaScript test framework used primarily for running unit and integration tests in Node.js and browser-based applications.
-
E.
Mocha
Mocha is a subsidiary peak of the Carihuairazo volcanic massif in the Ecuadorian Andes.
- F. None of above. chosen
Provenance (5 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada549aaa881908dcf92d20fa6f238 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235ad86288190850f6c355a187b26 |
completed | March 12, 2026, 3:40 a.m. |
| NEDg | Description generation | batch_69b236e4efe08190ade7c1cc4b941639 |
completed | March 12, 2026, 3:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2375a75488190b3f2215c85d43f9c |
completed | March 12, 2026, 3:47 a.m. |
Created at: March 8, 2026, 3:04 p.m.