Triple
T16499327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyoko Chan Cox |
E400761
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kyoko |
—
|
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: Kyoko | Statement: [Kyoko Chan Cox, givenName, Kyoko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyoko Context triple: [Kyoko Chan Cox, givenName, Kyoko]
-
A.
Kyoko
Kyoko is a mysterious, mostly silent android in the science fiction film "Ex Machina," serving as both assistant and unsettling presence within the reclusive inventor Nathan's isolated research facility.
-
B.
Kiyoko
Kiyoko is a Japanese feminine given name that can be written with various kanji combinations, often carrying meanings related to purity or respect.
-
C.
Keiko
Keiko was a famous captive orca best known for starring in the film "Free Willy" and later becoming the focus of a high-profile rehabilitation and release effort.
-
D.
Kyoko Sakura
chosen
Kyoko Sakura is a spear-wielding, food-loving magical girl known for her brash attitude and tragic past in the anime series Puella Magi Madoka Magica.
-
E.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e35b96881908c9d339eea9e4314 |
completed | April 18, 2026, 7:09 a.m. |
Created at: April 10, 2026, 5:14 a.m.