Triple
T23217715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Sayako |
E580795
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Princess Nori |
—
|
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: Princess Nori | Statement: [Princess Sayako, title, Princess Nori]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Princess Nori Context triple: [Princess Sayako, title, Princess Nori]
-
A.
Princess Nori
chosen
Princess Nori is the former title of Sayako Kuroda, the daughter of Japan’s Emperor Akihito and Empress Michiko, who left the imperial family upon her marriage to a commoner.
-
B.
Princess Toshi
Princess Toshi, formally Princess Aiko, is the only child of Emperor Naruhito and Empress Masako of Japan and a member of the Japanese imperial family.
-
C.
Princess Nukata
Princess Nukata was a 7th-century Japanese noblewoman and poet renowned for her waka poetry and prominent role in the early imperial court.
-
D.
Princess Yori
Princess Yori is a fictional royal character, also known as Princess Atsuko, who appears in Japanese-inspired storytelling and media.
-
E.
Princess Seishi
Princess Seishi was a Japanese imperial princess of the early Heian period who became the consort of Emperor Junna.
- 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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1916653f08190a7dcbc659c6b6a25 |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:08 p.m.