Triple
T5506874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atsuko |
E144461
|
entity |
| Predicate | hasNameVariant |
P457
|
FINISHED |
| Object | Atsuko (あつこ in hiragana) |
E144461
|
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: Atsuko (あつこ in hiragana) | Statement: [Atsuko, hasNameVariant, Atsuko (あつこ in hiragana)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atsuko (あつこ in hiragana) Context triple: [Atsuko, hasNameVariant, Atsuko (あつこ in hiragana)]
-
A.
Atsuko
chosen
Atsuko is a Japanese feminine given name commonly borne by women and princesses in Japan, with meanings that vary depending on the kanji used.
-
B.
Asaka
Asaka is a Japanese noble family name historically associated with a collateral branch of the Imperial Family, including Prince Asaka Yasuhiko.
-
C.
Haruko
Haruko, better known as Empress Shōken, was the consort of Emperor Meiji and a prominent Japanese empress noted for her support of modernization and social welfare.
-
D.
Naoko
Naoko is a central, emotionally fragile character in Haruki Murakami’s story "Norwegian Wood," whose complex relationship with the protagonist explores themes of love, loss, and mental illness.
-
E.
Masako
Masako is the Empress of Japan, a former diplomat and Harvard-educated member of the Imperial House known for her international background and public role.
- 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_69c008f6b5048190a09064116062cf69 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f47d2dc8190ad874be6902d8a4c |
completed | March 22, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c027bc39208190baa01feadb75d3c6 |
completed | March 22, 2026, 5:32 p.m. |
Created at: March 22, 2026, 3:32 p.m.