Triple
T2328019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naomi |
E48334
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Naomi (Japanese: なおみ, 直美, 尚美, etc.) |
E48334
|
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: Naomi (Japanese: なおみ, 直美, 尚美, etc.) | Statement: [Naomi, hasVariant, Naomi (Japanese: なおみ, 直美, 尚美, etc.)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naomi (Japanese: なおみ, 直美, 尚美, etc.) Context triple: [Naomi, hasVariant, Naomi (Japanese: なおみ, 直美, 尚美, etc.)]
-
A.
Naomi
chosen
Naomi is a feminine given name of Hebrew origin meaning "pleasantness" or "delight."
-
B.
Mayami
Mayami is a historical Native American people who lived around Lake Okeechobee in what is now southern Florida.
-
C.
Margaret Shinobu Awamura
Margaret Shinobu Awamura was the wife of long-serving U.S. Senator Daniel Inouye of Hawaii.
-
D.
Naoko Mori
Naoko Mori is a Japanese-born British actress best known for her roles in the TV series "Torchwood" and the musical "Miss Saigon."
-
E.
Naomi King
Naomi King is the daughter of renowned American horror novelist Stephen King.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc64c7f1881909b0d847f7782e803 |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae897243c48190a18b0e02ad664ead |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:50 p.m.