Triple
T19515801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Yakult Swallows |
E488273
|
entity |
| Predicate | mascot |
P52
|
FINISHED |
| Object | Tsubakuro |
—
|
NE NERFINISHED |
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: Tsubakuro | Statement: [Tokyo Yakult Swallows, mascot, Tsubakuro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsubakuro Context triple: [Tokyo Yakult Swallows, mascot, Tsubakuro]
-
A.
Tsubakuro
chosen
Tsubakuro is the popular swallow-themed mascot character of the Tokyo Yakult Swallows professional baseball team in Japan.
-
B.
Shimabukuro
Shimabukuro is a Japanese surname most notably associated with virtuoso ukulele player Jake Shimabukuro.
-
C.
Yotsugi
Yotsugi is a residential neighborhood in Tokyo, Japan, located within Katsushika Ward and known for its local shopping streets and traditional shitamachi atmosphere.
-
D.
Toyako
Toyako is a town in Hokkaido, Japan, known as a gateway to the scenic Lake Tōya area and nearby volcanic and hot spring attractions.
-
E.
Magome
Magome is a residential neighborhood in Tokyo known for its quiet streets and historical association with writers and literary figures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359b90f08190b38359dc9e97e11c |
completed | April 20, 2026, 2:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.