Triple
T16300449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akiko Takeshita |
E395769
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Akiko
Akiko is a Japanese feminine given name commonly used in Japan and among Japanese communities worldwide.
|
E1278673
|
NE FINISHED |
How this triple was built (4 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: Akiko | Statement: [Akiko Takeshita, givenName, Akiko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akiko Context triple: [Akiko Takeshita, givenName, Akiko]
-
A.
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.
-
B.
Misako
Misako is a key character in the Ninjago universe, known as an archaeologist and historian who is the mother of Lloyd Garmadon and the wife of Garmadon.
-
C.
Chikako
Chikako is a Japanese feminine given name that can be written with various kanji characters and is borne by several notable women in Japan.
-
D.
Sachiko
Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Akiko Triple: [Akiko Takeshita, givenName, Akiko]
Generated description
Akiko is a Japanese feminine given name commonly used in Japan and among Japanese communities worldwide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Akiko Target entity description: Akiko is a Japanese feminine given name commonly used in Japan and among Japanese communities worldwide.
-
A.
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.
-
B.
Misako
Misako is a key character in the Ninjago universe, known as an archaeologist and historian who is the mother of Lloyd Garmadon and the wife of Garmadon.
-
C.
Chikako
Chikako is a Japanese feminine given name that can be written with various kanji characters and is borne by several notable women in Japan.
-
D.
Sachiko
Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
-
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. chosen
Provenance (5 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e31c9e8819094593f3aeb44f2ca |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01e7ff14dc819086042db64d41f5c2 |
completed | May 11, 2026, 2:30 p.m. |
| NEDg | Description generation | batch_6a01eed32bbc81908ea9e2588e3741f8 |
completed | May 11, 2026, 2:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01ef6edb7c81908bdbf4d42dd6b9aa |
completed | May 11, 2026, 3:02 p.m. |
Created at: April 10, 2026, 5:06 a.m.