Triple
T493724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iwakura Mission |
E10243
|
entity |
| Predicate | studiedField |
P1945
|
FINISHED |
| Object | political systems |
—
|
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: political systems | Statement: [Iwakura Mission, studiedField, political systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studiedField Context triple: [Iwakura Mission, studiedField, political systems]
-
A.
offersFieldOfStudy
Indicates that an institution or program provides a particular field of study as an available area of academic focus.
-
B.
studiedUnder
Indicates that one entity received instruction, training, or mentorship from another, typically in an academic or apprenticeship context.
-
C.
studiedBy
chosen
Indicates that a subject (such as a field, topic, or object) is examined, researched, or learned by an agent (such as a person or group).
-
D.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
E.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0fbfa408190aeb3b93996a35c00 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf90ca88190b6a182e5b6733612 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.