Triple
T13749150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darryl Hill |
E330294
|
entity |
| Predicate | notableAlias |
P39
|
FINISHED |
| Object | Cappachino |
E330296
|
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: Cappachino | Statement: [Darryl Hill, notableAlias, Cappachino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cappachino Context triple: [Darryl Hill, notableAlias, Cappachino]
-
A.
Cappachino
chosen
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.
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.
-
D.
Crema
Crema is a historic town in the Lombardy region of northern Italy, known for its medieval architecture and cultural heritage.
-
E.
Caffè Torino
Caffè Torino is a historic and elegant café in Turin, Italy, renowned for its classic Belle Époque atmosphere and role as a traditional meeting place for locals and visitors.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02132a108190aca728b95e83af01 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a854098c8190983d142c9930962b |
completed | May 3, 2026, 7:56 p.m. |
Created at: April 9, 2026, 10:08 p.m.