Triple
T19411463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korean dalgona candy |
E485596
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | dalgona |
—
|
NE NERFINISHED |
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: dalgona | Statement: [Korean dalgona candy, alsoKnownAs, dalgona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: dalgona Context triple: [Korean dalgona candy, alsoKnownAs, dalgona]
-
A.
Dalgona challenge
The Dalgona challenge is a viral game popularized by the series "Squid Game," in which participants must carefully cut out a shape from a thin Korean honeycomb candy without breaking it.
-
B.
Korean dalgona candy
chosen
Korean dalgona candy is a traditional Korean street sweet made from melted sugar and baking soda, known for its light, honeycomb-like texture and often stamped shapes.
-
C.
Chocina
Chocina is a river in northern Poland that serves as a tributary of the Brda River.
-
D.
Crema
Crema is a historic town in the Lombardy region of northern Italy, known for its medieval architecture and cultural heritage.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af681288190ba2ec52d5adb6a22 |
completed | April 20, 2026, 1:32 p.m. |
Created at: April 10, 2026, 1:37 p.m.