Triple
T3129684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cappadonna |
E65379
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Cappuccino |
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: Cappuccino | Statement: [Cappadonna, alsoKnownAs, Cappuccino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cappuccino Context triple: [Cappadonna, alsoKnownAs, Cappuccino]
-
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.
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.
- 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_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_69b224d860dc819095a864619bc29411 |
completed | March 12, 2026, 2:28 a.m. |
Created at: March 8, 2026, 3:04 p.m.