Triple
T8919225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzuki |
E212368
|
entity |
| Predicate | rankByCommonnessInJapan |
P86407
|
FINISHED |
| Object | among most common surnames |
—
|
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: among most common surnames | Statement: [Suzuki, rankByCommonnessInJapan, among most common surnames]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByCommonnessInJapan Context triple: [Suzuki, rankByCommonnessInJapan, among most common surnames]
-
A.
nameOrderInJapan
Indicates that the person’s name is written or presented in the Japanese order, with the family name appearing before the given name.
-
B.
rankingByHeightInJapan
Indicates the relative order of entities based on their height specifically within the context of Japan.
-
C.
gdpRankInJapan
Indicates the position of an entity in the ordered ranking of GDP values within Japan.
-
D.
eraNumberInJapan
Indicates the specific numbered position of a historical era within the sequence of Japanese eras.
-
E.
eraNameInJapanese
Indicates the Japanese-language name used for a specific historical or calendar era.
- 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_69ca8393b1808190bd4336787ffa2c40 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6613639881909090d060f388a865 |
completed | April 1, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed0ef3c81908cc69eac852ee12a |
completed | March 31, 2026, 11:54 p.m. |
| PDg | Predicate description generation | batch_69cc600a59708190ae426044bbcd7929 |
completed | April 1, 2026, midnight |
Created at: March 30, 2026, 6:56 p.m.