Triple
T15258250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kei Komuro |
E364702
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kei |
E961486
|
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: Kei | Statement: [Kei Komuro, givenName, Kei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kei Context triple: [Kei Komuro, givenName, Kei]
-
A.
Kei
chosen
Kei is a common given name used in various cultures, including Japanese and some African communities, for both males and females.
-
B.
Keiun
Keiun was a Japanese era name (nengō) from the early 8th century, used during the reign of Emperor Monmu.
-
C.
Youki Kudoh
Youki Kudoh is a Japanese actress and singer known internationally for her roles in films such as "Mystery Train," "Heaven's Burning," and "Snow Falling on Cedars."
-
D.
Isami
Isami was a 14th-century Indian historian and poet best known for his Persian chronicle "Futuh-us-Salatin," which records the political and military history of the Delhi Sultanate, including the Mongol invasions of India.
-
E.
Makoto
Makoto is a common Japanese given name used for people of any gender, often associated with sincerity or truth.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084d11148190919eef8e55569bb9 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef6def4c8190b6aed1f68d336c5a |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:13 a.m.