Triple
T8777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan |
E174
|
entity |
| Predicate | hasAdvancedTechnologySector |
P759
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Japan, hasAdvancedTechnologySector, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdvancedTechnologySector Context triple: [Japan, hasAdvancedTechnologySector, yes]
-
A.
hasInnovationHub
Indicates that an entity hosts, contains, or is associated with a dedicated center or facility focused on innovation activities.
-
B.
hasTechnicalSociety
Indicates that an entity is associated with, or possesses membership in, a technical or engineering-focused society or organization.
-
C.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
D.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
E.
technologyParadigm
Indicates a relationship where one entity represents or defines the overarching technological model, framework, or approach within which another entity operates or is categorized.
- F. None of above. chosen
Provenance (4 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a240b249788190af8dbf7e80e9c91b |
completed | Feb. 28, 2026, 1:11 a.m. |
| PD | Predicate disambiguation | batch_69a23fe52ec48190a4d24101c91434ed |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a240b1551c81908abcae128ea45d00 |
completed | Feb. 28, 2026, 1:11 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.