Triple
T20903493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toru Watanabe |
E514730
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Naoko |
—
|
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: Naoko | Statement: [Toru Watanabe, associatedWith, Naoko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naoko Context triple: [Toru Watanabe, associatedWith, Naoko]
-
A.
Naoko
chosen
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.
-
B.
Ayako
Ayako is a Japanese feminine given name commonly used for women and girls in Japan.
-
C.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
D.
Noriko
Noriko is a common Japanese feminine given name, often written with kanji conveying meanings such as "law," "order," or "child."
-
E.
Atsuko
Atsuko is a Japanese feminine given name commonly borne by women and princesses in Japan, with meanings that vary depending on the kanji used.
- 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8fe4b808190bbc1bbde7a11f283 |
completed | April 21, 2026, 3:03 a.m. |
Created at: April 16, 2026, 12:47 p.m.