Triple
T26340795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaga Hyakumangoku |
E662639
|
entity |
| Predicate | economicRankInJapan |
P137097
|
FINISHED |
| Object | one of the wealthiest domains |
—
|
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: one of the wealthiest domains | Statement: [Kaga Hyakumangoku, economicRankInJapan, one of the wealthiest domains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicRankInJapan Context triple: [Kaga Hyakumangoku, economicRankInJapan, one of the wealthiest domains]
-
A.
gdpRankInJapan
Indicates the position of an entity in the ordered ranking of GDP values within Japan.
-
B.
rankWithinJapan
chosen
Indicates the relative position or standing of something when compared only among counterparts within Japan.
-
C.
rankByCommonnessInJapan
Indicates how items are ordered based on how commonly they occur or are found in Japan.
-
D.
areaRankingInJapan
Indicates the relative position of an entity in a size-based ranking within Japan.
-
E.
ratingJapan
Indicates that an entity assigns or holds a rating specifically related to Japan (e.g., its products, services, or overall experience).
- 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_69ee81304194819092e20e0fae3aee07 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 26, 2026, 10:38 p.m.