Triple
T8482441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Go |
E200551
|
entity |
| Predicate | majorRuleSet |
P8188
|
FINISHED |
| Object | Japanese rules |
—
|
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: Japanese rules | Statement: [Go, majorRuleSet, Japanese rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorRuleSet Context triple: [Go, majorRuleSet, Japanese rules]
-
A.
majorFor
Indicates that an academic program, field of study, or specialization is the primary major associated with a particular student or degree.
-
B.
setsRulesFor
chosen
Indicates that one entity establishes or defines rules, guidelines, or constraints that another entity is expected to follow.
-
C.
majorPolicy
Indicates a relationship where a policy is classified as a primary or highly significant guiding rule or course of action within a system or organization.
-
D.
majorStyle
Indicates the primary artistic, aesthetic, or methodological style that characterizes or dominates something in relation to others.
-
E.
majorCase
Indicates that a legal case is of primary importance or high significance within a given context.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53638c48190b742fc51d1b4442a |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:12 p.m.