Triple
T9161054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kodama |
E219821
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Kodama Yuta
Kodama Yuta is a Japanese individual notable for bearing the surname Kodama, though specific widely recognized public achievements or roles under this name are not well documented.
|
E786617
|
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: Kodama Yuta | Statement: [Kodama, hasNotableBearer, Kodama Yuta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kodama Yuta Context triple: [Kodama, hasNotableBearer, Kodama Yuta]
-
A.
Kodama Kazuto
Kodama Kazuto is a Japanese individual notable enough to be specifically distinguished as a bearer of the surname Kodama.
-
B.
Yuji
Yuji is a common Japanese masculine given name used by various real and fictional individuals.
-
C.
Mitsuru
Mitsuru is a Japanese given name that can be used for people of any gender and is borne by various notable figures in sports, arts, and entertainment.
-
D.
Shioli Kutsuna
Shioli Kutsuna is a Japanese-Australian actress known for roles in international films and series, including major Hollywood productions and high-profile video game projects.
-
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. 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: Kodama Yuta Triple: [Kodama, hasNotableBearer, Kodama Yuta]
Generated description
Kodama Yuta is a Japanese individual notable for bearing the surname Kodama, though specific widely recognized public achievements or roles under this name are not well documented.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kodama Yuta Target entity description: Kodama Yuta is a Japanese individual notable for bearing the surname Kodama, though specific widely recognized public achievements or roles under this name are not well documented.
-
A.
Kodama Kazuto
Kodama Kazuto is a Japanese individual notable enough to be specifically distinguished as a bearer of the surname Kodama.
-
B.
Yuji
Yuji is a common Japanese masculine given name used by various real and fictional individuals.
-
C.
Mitsuru
Mitsuru is a Japanese given name that can be used for people of any gender and is borne by various notable figures in sports, arts, and entertainment.
-
D.
Shioli Kutsuna
Shioli Kutsuna is a Japanese-Australian actress known for roles in international films and series, including major Hollywood productions and high-profile video game projects.
-
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. 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2ac0508190b2f5c801c2c26d66 |
completed | April 1, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d07768fcd48190b7d4181e57f49753 |
completed | April 4, 2026, 2:28 a.m. |
| NEDg | Description generation | batch_69d07ba6ca3881909aa43516a3ac0272 |
completed | April 4, 2026, 2:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d07c04ab98819092a2d515c7b1baaa |
completed | April 4, 2026, 2:48 a.m. |
Created at: March 30, 2026, 7:21 p.m.