Triple
T20446416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alola |
E501527
|
entity |
| Predicate | hasMythicalPokémon |
P86125
|
FINISHED |
| Object |
Magearna
Magearna is a Mythical Steel/Fairy-type Pokémon resembling a mechanical doll, known for its artificial creation and the life-giving Soul-Heart at its core.
|
E1431806
|
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: Magearna | Statement: [Alola, hasMythicalPokémon, Magearna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magearna Context triple: [Alola, hasMythicalPokémon, Magearna]
-
A.
Meraxes
Meraxes was one of the great dragons of House Targaryen, ridden by Queen Rhaenys during the wars that forged the Targaryen rule over Westeros.
-
B.
Mago
Mago is a rural settlement located within the Nikolaevsky District of Russia’s Khabarovsk Krai.
-
C.
Dramaga
Dramaga is a district in West Java, Indonesia, known for hosting the main campus of Bogor Agricultural University (IPB) and forming part of the greater Bogor area.
-
D.
Magath
Magath is a German surname most notably associated with Felix Magath, a former professional footballer and successful Bundesliga coach.
-
E.
Taralga
Taralga is a small rural village in New South Wales, Australia, known for its historic buildings, sheep and cattle farming, and proximity to the Wombeyan Caves.
- 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: Magearna Triple: [Alola, hasMythicalPokémon, Magearna]
Generated description
Magearna is a Mythical Steel/Fairy-type Pokémon resembling a mechanical doll, known for its artificial creation and the life-giving Soul-Heart at its core.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magearna Target entity description: Magearna is a Mythical Steel/Fairy-type Pokémon resembling a mechanical doll, known for its artificial creation and the life-giving Soul-Heart at its core.
-
A.
Meraxes
Meraxes was one of the great dragons of House Targaryen, ridden by Queen Rhaenys during the wars that forged the Targaryen rule over Westeros.
-
B.
Mago
Mago is a rural settlement located within the Nikolaevsky District of Russia’s Khabarovsk Krai.
-
C.
Dramaga
Dramaga is a district in West Java, Indonesia, known for hosting the main campus of Bogor Agricultural University (IPB) and forming part of the greater Bogor area.
-
D.
Magath
Magath is a German surname most notably associated with Felix Magath, a former professional footballer and successful Bundesliga coach.
-
E.
Taralga
Taralga is a small rural village in New South Wales, Australia, known for its historic buildings, sheep and cattle farming, and proximity to the Wombeyan Caves.
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfd84c08190a3f971f1cd279715 |
completed | April 20, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0884056b4c81909d06e4cbba56533f |
completed | May 16, 2026, 2:49 p.m. |
| NEDg | Description generation | batch_6a0886c7b794819091e4b7915bcbe858 |
completed | May 16, 2026, 3:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08876380048190aa9d0e20f3752a0f |
completed | May 16, 2026, 3:04 p.m. |
Created at: April 16, 2026, 11:32 a.m.