Triple
T8037494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Okayama |
E187143
|
entity |
| Predicate | hasPopulationRankInPrefecture |
P25930
|
FINISHED |
| Object | largest city in Okayama Prefecture |
—
|
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: largest city in Okayama Prefecture | Statement: [Okayama, hasPopulationRankInPrefecture, largest city in Okayama Prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationRankInPrefecture Context triple: [Okayama, hasPopulationRankInPrefecture, largest city in Okayama Prefecture]
-
A.
populationRankInAichiPrefecture
Indicates the relative position of an entity in terms of population size compared to other entities within Aichi Prefecture.
-
B.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
isPrefecturalCityOf
Indicates that a city holds the administrative status of a prefecture-level city within a given region or country.
-
D.
hasPopulationRankInRegion
chosen
Indicates that an entity has a specific population-based rank or position within a defined geographic region.
-
E.
gdpRankInJapan
Indicates the position of an entity in the ordered ranking of GDP values within Japan.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f188e1c8190b92760c91d31f2df |
completed | March 31, 2026, 3:27 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:23 p.m.