Triple
T4977484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honeycomb (Dalgona) challenge |
E111802
|
entity |
| Predicate | hasRiskInFiction |
P60749
|
FINISHED |
| Object | death |
—
|
LITERAL 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: death | Statement: [Honeycomb (Dalgona) challenge, hasRiskInFiction, death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiskInFiction Context triple: [Honeycomb (Dalgona) challenge, hasRiskInFiction, death]
-
A.
hasReputationInFiction
Indicates that an entity is known or regarded in a particular way within fictional works or narratives.
-
B.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
C.
associatedWithCaseInFiction
Indicates that an entity is connected to, involved in, or relevant to a particular case or investigation within a fictional context.
-
D.
hasUnreliableNarrator
Indicates that the story is told by a narrator whose account cannot be fully trusted due to bias, limited knowledge, deception, or instability.
-
E.
hasFictionalSubstance
Indicates that one entity includes, contains, or involves a fictional or imaginary substance as part of its composition, setting, or narrative.
- F. None of above. chosen
Provenance (4 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:33 p.m.