Triple
T4101092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mudbound |
E87941
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object |
Mako Kamitsuna
Mako Kamitsuna is a Japanese-born film editor and filmmaker known for her work on critically acclaimed independent films, including the period drama "Mudbound."
|
E475710
|
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: Mako Kamitsuna | Statement: [Mudbound, editor, Mako Kamitsuna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mako Kamitsuna Context triple: [Mudbound, editor, Mako Kamitsuna]
-
A.
Masayuki
Masayuki is a Japanese given name commonly used for males.
-
B.
Masahito
Masahito is the personal name of Prince Hitachi, a member of the Japanese imperial family and younger brother of Emperor Emeritus Akihito.
-
C.
Hiranuma
Hiranuma is a notable district within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
-
D.
Akinobu
Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
-
E.
Shintaro
Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
- 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: Mako Kamitsuna Triple: [Mudbound, editor, Mako Kamitsuna]
Generated description
Mako Kamitsuna is a Japanese-born film editor and filmmaker known for her work on critically acclaimed independent films, including the period drama "Mudbound."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mako Kamitsuna Target entity description: Mako Kamitsuna is a Japanese-born film editor and filmmaker known for her work on critically acclaimed independent films, including the period drama "Mudbound."
-
A.
Masayuki
Masayuki is a Japanese given name commonly used for males.
-
B.
Masahito
Masahito is the personal name of Prince Hitachi, a member of the Japanese imperial family and younger brother of Emperor Emeritus Akihito.
-
C.
Hiranuma
Hiranuma is a notable district within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
-
D.
Akinobu
Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
-
E.
Shintaro
Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
- 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_69aed94564cc8190a9c1457daedb6e7f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0ed168819093c83ba079d6725c |
completed | March 9, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67ac56548190a2d52b055cb48e8e |
completed | March 21, 2026, 9:41 a.m. |
| NEDg | Description generation | batch_69be682cfe548190b657e0f1694a1142 |
completed | March 21, 2026, 9:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be68a634c08190aadfc362199a8d7e |
completed | March 21, 2026, 9:45 a.m. |
Created at: March 9, 2026, 3:40 p.m.