Triple
T18367264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Kaguya |
E440079
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Kaguya-hime |
—
|
NE NERFINISHED |
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: Kaguya-hime | Statement: [Princess Kaguya, alsoKnownAs, Kaguya-hime]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaguya-hime Context triple: [Princess Kaguya, alsoKnownAs, Kaguya-hime]
-
A.
Kaguya
Kaguya is a Japanese lunar orbiter mission by JAXA that conducted detailed mapping and scientific investigation of the Moon’s surface and gravitational field.
-
B.
Princess Kaguya
chosen
Princess Kaguya is the moon princess from the classic Japanese folktale "The Tale of the Bamboo Cutter," renowned as one of Japan’s oldest and most famous literary works.
-
C.
Yakami-hime
Yakami-hime is a goddess in Japanese mythology known as a consort of the deity Ōkuninushi and as a figure in the Izumo cycle of legends.
-
D.
Tamayori-hime
Tamayori-hime is a goddess in Japanese mythology, often associated with water and the sea, revered as the mother of Japan’s legendary first emperor, Emperor Jimmu.
-
E.
Hidaka-hime
Hidaka-hime is the birth name of Empress Genshō, a Nara-period Japanese empress who ruled in the early 8th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5174f5f448190a1fc67d3039aadd9 |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 10:38 a.m.