Triple
T7006002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tohoku Rakuten Golden Eagles |
E162457
|
entity |
| Predicate | japanSeriesTitle |
P6227
|
FINISHED |
| Object | 2013 Japan Series |
—
|
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: 2013 Japan Series | Statement: [Tohoku Rakuten Golden Eagles, japanSeriesTitle, 2013 Japan Series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: japanSeriesTitle Context triple: [Tohoku Rakuten Golden Eagles, japanSeriesTitle, 2013 Japan Series]
-
A.
titleInJapanese
Indicates that one entity is the title of another entity expressed specifically in the Japanese language.
-
B.
JapanSeriesTitles
Indicates that the subject is a title belonging to a series originating from or specifically released in Japan.
-
C.
JapanSeriesTitle
chosen
Indicates that the given title is the name used for a series in Japan.
-
D.
JapanSeriesTitleCount
Indicates the number of series titles associated with or released in Japan.
-
E.
equivalentTitleInJapanese
Indicates that one entity has a corresponding or matching title in Japanese that is equivalent in meaning or usage to the other entity’s title.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc34b5a88190a793e07dd4d0018b |
completed | March 27, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.