Triple
T10939753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kagawa Prefecture |
E258435
|
entity |
| Predicate | areaRankingInJapan |
P96746
|
FINISHED |
| Object | 47 |
—
|
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: 47 | Statement: [Kagawa Prefecture, areaRankingInJapan, 47]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankingInJapan Context triple: [Kagawa Prefecture, areaRankingInJapan, 47]
-
A.
populationRankInAichiPrefecture
Indicates the relative position of an entity in terms of population size compared to other entities within Aichi Prefecture.
-
B.
gdpRankInJapan
Indicates the position of an entity in the ordered ranking of GDP values within Japan.
-
C.
relativeSizeAmongJapanMainIslands
Indicates the comparative size ranking of an island relative to the other main islands of Japan.
-
D.
isPrefecturalCityOf
Indicates that a city holds the administrative status of a prefecture-level city within a given region or country.
-
E.
rankingByHeightInJapan
Indicates the relative order of entities based on their height specifically within the context of Japan.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c1389881909341170984211810 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.