Triple
T15132755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot Shower |
E361459
|
entity |
| Predicate | recordingArtist |
P5936
|
FINISHED |
| Object | MadeinTYO |
E1069200
|
NE 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: MadeinTYO | Statement: [Hot Shower, recordingArtist, MadeinTYO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MadeinTYO Context triple: [Hot Shower, recordingArtist, MadeinTYO]
-
A.
MadeinTYO
chosen
MadeinTYO is an American rapper and songwriter best known for his breakout hit "Uber Everywhere" and his melodic, laid-back trap style.
-
B.
TYO
TYO is the metropolitan airport code representing the Tokyo area’s major airports, primarily Haneda (HND) and Narita (NRT).
-
C.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
-
D.
Shibuya 109
Shibuya 109 is a famous multi-story fashion shopping mall in Tokyo known as a trendsetting hub for youth and street fashion.
-
E.
Tokyo Solamachi
Tokyo Solamachi is a large shopping, dining, and entertainment complex located at the base of Tokyo Skytree in Tokyo, Japan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b29a4c819087f8818e3f5788f5 |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec88096f081908897fd1c5362c274 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:06 a.m.