Triple
T11225831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crash Team Racing Nitro-Fueled |
E265689
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Polar
Polar is a small, friendly polar bear character and playable racer in the Crash Bandicoot kart-racing games.
|
E912523
|
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: Polar | Statement: [Crash Team Racing Nitro-Fueled, hasCharacter, Polar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Polar Context triple: [Crash Team Racing Nitro-Fueled, hasCharacter, Polar]
-
A.
Polar
Polar is a 2019 action-thriller film directed by Jonas Åkerlund, based on the Dark Horse graphic novel about an aging assassin forced out of retirement.
-
B.
Polar
Polar is a record label associated with the Swedish company Polar Music, known for releasing music by prominent Scandinavian artists.
-
C.
Polar Frontier
Polar Frontier is an Arctic-themed exhibit at the Columbus Zoo and Aquarium that showcases polar bears and other cold-climate wildlife in naturalistic habitats.
-
D.
Polyarny
Polyarny is a Russian naval town in Murmansk Oblast known as a key base for the Northern Fleet and submarine operations in the Arctic region.
-
E.
Polaria
Polaria is an Arctic-themed experience center and aquarium in Tromsø, Norway, focusing on polar research, climate, and marine life.
- 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: Polar Triple: [Crash Team Racing Nitro-Fueled, hasCharacter, Polar]
Generated description
Polar is a small, friendly polar bear character and playable racer in the Crash Bandicoot kart-racing games.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Polar Target entity description: Polar is a small, friendly polar bear character and playable racer in the Crash Bandicoot kart-racing games.
-
A.
Polar
Polar is a 2019 action-thriller film directed by Jonas Åkerlund, based on the Dark Horse graphic novel about an aging assassin forced out of retirement.
-
B.
Polar
Polar is a record label associated with the Swedish company Polar Music, known for releasing music by prominent Scandinavian artists.
-
C.
Polar Frontier
Polar Frontier is an Arctic-themed exhibit at the Columbus Zoo and Aquarium that showcases polar bears and other cold-climate wildlife in naturalistic habitats.
-
D.
Polyarny
Polyarny is a Russian naval town in Murmansk Oblast known as a key base for the Northern Fleet and submarine operations in the Arctic region.
-
E.
Polaria
Polaria is an Arctic-themed experience center and aquarium in Tromsø, Norway, focusing on polar research, climate, and marine life.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ee15d4819087449058addef597 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad269b248190bb72e560e3efc0ce |
completed | April 19, 2026, 10:23 a.m. |
| NEDg | Description generation | batch_69e4b12c04e48190ad7546d556a5109f |
completed | April 19, 2026, 10:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4b2949c7c8190820b7f1f87e00602 |
completed | April 19, 2026, 10:46 a.m. |
Created at: April 8, 2026, 9:30 p.m.