Triple
T710163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Representatives of Japan |
E14187
|
entity |
| Predicate | jointSessionPurpose |
P3082
|
FINISHED |
| Object | electing the Prime Minister |
—
|
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: electing the Prime Minister | Statement: [House of Representatives of Japan, jointSessionPurpose, electing the Prime Minister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jointSessionPurpose Context triple: [House of Representatives of Japan, jointSessionPurpose, electing the Prime Minister]
-
A.
meetsBetweenSessionsOf
Indicates that one entity meets another during the interval between scheduled sessions or events.
-
B.
hasJointSessionName
Indicates that an entity is associated with a specific joint session identified by a particular name.
-
C.
meetingType
chosen
Indicates the specific category or format of a meeting that characterizes how it is organized or conducted.
-
D.
convenesRegularSession
Indicates that an entity formally brings together a group or body for its routine or scheduled meeting.
-
E.
convenesIn
Indicates that an entity brings together or assembles a group, meeting, or event at a specific place or venue.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c011948190b2cfccd8fe722742 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f0217081908268b3f47e72f8df |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.