Triple
T3352814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ōkubo Toshimichi |
E70534
|
entity |
| Predicate | reasonForTravel |
P24037
|
FINISHED |
| Object | study Western political and economic 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: study Western political and economic systems | Statement: [Ōkubo Toshimichi, reasonForTravel, study Western political and economic systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForTravel Context triple: [Ōkubo Toshimichi, reasonForTravel, study Western political and economic systems]
-
A.
typicalJourneyPurpose
chosen
Indicates the usual or most common reason or objective for which an entity undertakes a journey.
-
B.
sunJourneyPurpose
Indicates the purpose or intended goal behind a sun-related journey or movement.
-
C.
coTraveler
Indicates that two or more entities are traveling together along (part of) the same journey or route.
-
D.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
-
E.
involvedTravelBetween
Indicates a relationship where an entity participates in or is associated with travel occurring between two specified locations.
- 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb23ec53881908a04c7f784fe8c43 |
completed | March 8, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69ada42fbe7c8190b9f185b5ab985f17 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.