Triple
T15244655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurtigruten AS |
E364347
|
entity |
| Predicate | hasShip |
P14595
|
FINISHED |
| Object |
MS Polarlys
MS Polarlys is a Norwegian coastal passenger and cargo ship operated on the Hurtigruten route along Norway’s coastline.
|
E1145549
|
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: MS Polarlys | Statement: [Hurtigruten AS, hasShip, MS Polarlys]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MS Polarlys Context triple: [Hurtigruten AS, hasShip, MS Polarlys]
-
A.
Polar Horizon
Polar Horizon is a themed attraction area at Chimelong Ocean Kingdom that immerses visitors in polar-inspired environments and marine wildlife exhibits.
-
B.
Polar
Polar is a small, friendly polar bear character and playable racer in the Crash Bandicoot kart-racing games.
-
C.
Polar
Polar was a NASA scientific research satellite dedicated to studying Earth's polar magnetosphere and auroral phenomena as part of the International Solar–Terrestrial Physics program.
-
D.
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.
-
E.
Polar
Polar is a record label associated with the Swedish company Polar Music, known for releasing music by prominent Scandinavian artists.
- 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: MS Polarlys Triple: [Hurtigruten AS, hasShip, MS Polarlys]
Generated description
MS Polarlys is a Norwegian coastal passenger and cargo ship operated on the Hurtigruten route along Norway’s coastline.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MS Polarlys Target entity description: MS Polarlys is a Norwegian coastal passenger and cargo ship operated on the Hurtigruten route along Norway’s coastline.
-
A.
Polar Horizon
Polar Horizon is a themed attraction area at Chimelong Ocean Kingdom that immerses visitors in polar-inspired environments and marine wildlife exhibits.
-
B.
Polar
Polar is a small, friendly polar bear character and playable racer in the Crash Bandicoot kart-racing games.
-
C.
Polar
Polar was a NASA scientific research satellite dedicated to studying Earth's polar magnetosphere and auroral phenomena as part of the International Solar–Terrestrial Physics program.
-
D.
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.
-
E.
Polar
Polar is a record label associated with the Swedish company Polar Music, known for releasing music by prominent Scandinavian artists.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f306f08190be448b215d6c9b6c |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd461cf08190a506aac2f0cec83a |
completed | May 9, 2026, 7:07 a.m. |
| NEDg | Description generation | batch_69fedf6ee3f081909553078cd3e9d243 |
completed | May 9, 2026, 7:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fee0016a088190ad87268e035f677e |
completed | May 9, 2026, 7:19 a.m. |
Created at: April 10, 2026, 3:13 a.m.