Triple
T30020714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shizuka Arakawa |
E762727
|
entity |
| Predicate | field of study |
P36625
|
FINISHED |
| Object | social sciences |
—
|
LITERAL 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: social sciences | Statement: [Shizuka Arakawa, field of study, social sciences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: field of study Context triple: [Shizuka Arakawa, field of study, social sciences]
-
A.
dimensionOfStudy
Indicates the specific field, aspect, or perspective that characterizes or structures a particular study or research activity.
-
B.
characterFieldOfStudy
Indicates the academic or disciplinary field that a character studies or specializes in.
-
C.
regionOfStudy
Indicates the academic or research area that is the focus of someone’s study or investigation.
-
D.
partOfStudy
Indicates that something is a component, segment, or subset within a larger study or research project.
-
E.
hasSubjectOfStudy
chosen
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
- F. None of above.
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_69f2246ee6e48190b69e837b913b398a |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 29, 2026, 6:47 p.m.