Triple
T9602717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo metropolitan area |
E231887
|
entity |
| Predicate | gdpRank |
P89177
|
FINISHED |
| Object | one of the largest metropolitan economies in the world |
—
|
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 largest metropolitan economies in the world | Statement: [Tokyo metropolitan area, gdpRank, one of the largest metropolitan economies in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gdpRank Context triple: [Tokyo metropolitan area, gdpRank, one of the largest metropolitan economies in the world]
-
A.
GDPPerCapitaRanking
Indicates the relative position of an entity in an ordered list based on its gross domestic product (GDP) per person.
-
B.
gdpRankInUS
Indicates the relative position of an entity in the ranking of U.S. entities based on their Gross Domestic Product (GDP).
-
C.
wealthRanking
Indicates the relative ordering of entities based on their level of wealth or financial resources.
-
D.
countryRanking
Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
-
E.
gdpRankInJapan
Indicates the position of an entity in the ordered ranking of GDP values within 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_69ca8484838c8190b2049199d22fef70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a5af8f0819089408ed630afa812 |
completed | April 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a6fd2481908efd131e207b8143 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:08 p.m.