Triple
T7644173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Arendelle |
E173079
|
entity |
| Predicate | hasEvent |
P811
|
FINISHED |
| Object |
Great Freeze
The Great Freeze is a catastrophic magical winter in Disney's Frozen universe that engulfs the Kingdom of Arendelle in ice and snow after Queen Elsa’s powers spiral out of control.
|
E677924
|
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: Great Freeze | Statement: [Kingdom of Arendelle, hasEvent, Great Freeze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Great Freeze Context triple: [Kingdom of Arendelle, hasEvent, Great Freeze]
-
A.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
B.
Thaw
Thaw is a surname most notably associated with English actor John Thaw, famed for his role as Inspector Morse.
-
C.
Glacier Freeze
Glacier Freeze is a popular cool, berry-flavored variety of Gatorade sports drink known for its light blue color and refreshing taste.
-
D.
Frost
Frost is a common English surname borne by numerous notable individuals, including the American poet Robert Frost.
-
E.
Frost
Frost is the middle name of George F. Kennan, the influential American diplomat and historian known for shaping the U.S. Cold War containment strategy.
- 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: Great Freeze Triple: [Kingdom of Arendelle, hasEvent, Great Freeze]
Generated description
The Great Freeze is a catastrophic magical winter in Disney's Frozen universe that engulfs the Kingdom of Arendelle in ice and snow after Queen Elsa’s powers spiral out of control.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Great Freeze Target entity description: The Great Freeze is a catastrophic magical winter in Disney's Frozen universe that engulfs the Kingdom of Arendelle in ice and snow after Queen Elsa’s powers spiral out of control.
-
A.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
B.
Thaw
Thaw is a surname most notably associated with English actor John Thaw, famed for his role as Inspector Morse.
-
C.
Glacier Freeze
Glacier Freeze is a popular cool, berry-flavored variety of Gatorade sports drink known for its light blue color and refreshing taste.
-
D.
Frost
Frost is a common English surname borne by numerous notable individuals, including the American poet Robert Frost.
-
E.
Frost
Frost is the middle name of George F. Kennan, the influential American diplomat and historian known for shaping the U.S. Cold War containment strategy.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf13858819095262664e1e04eb7 |
completed | March 27, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870d510f08190ad7706f582e8c1a0 |
completed | March 29, 2026, 12:22 a.m. |
| NEDg | Description generation | batch_69c87328c2cc81908b9fb89f5fee062e |
completed | March 29, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c873846a188190a3a1cc56ac247fb0 |
completed | March 29, 2026, 12:34 a.m. |
Created at: March 27, 2026, 3:58 p.m.