Triple
T15999961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skies of Arcadia |
E388067
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Aika |
E1187795
|
NE 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: Aika | Statement: [Skies of Arcadia, mainCharacter, Aika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aika Context triple: [Skies of Arcadia, mainCharacter, Aika]
-
A.
Aika
chosen
Aika is a spirited, red-haired air pirate and close companion of Vyse in the role-playing game Skies of Arcadia.
-
B.
Tempi
Tempi is a municipality in the Thessaly region of central Greece, known for its scenic location near the Vale of Tempe and along the Pinios River.
-
C.
Timet
Timet is a leading global producer and supplier of titanium metal products used primarily in aerospace, industrial, and military applications.
-
D.
Vremya
Vremya is a Russian publishing house known for releasing literary works, including notable Russian novels.
-
E.
Vremya
Vremya is a long-running Soviet and later Russian national television news program that served as the primary evening newscast on state TV.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1578a0adc819097c6a23514182173 |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf1edc7c81908fdd0fa00418d7a7 |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:55 a.m.