Triple
T13931531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beach House 3 |
E335002
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object |
MadeinTYO
MadeinTYO is an American rapper and songwriter best known for his breakout hit "Uber Everywhere" and his melodic, laid-back trap style.
|
E1069200
|
NE FINISHED |
How this triple was built (4 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: [Beach House 3, featuresArtist, MadeinTYO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MadeinTYO Context triple: [Beach House 3, featuresArtist, MadeinTYO]
-
A.
TYO
TYO is the metropolitan airport code representing the Tokyo area’s major airports, primarily Haneda (HND) and Narita (NRT).
-
B.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
-
C.
Shibuya 109
Shibuya 109 is a famous multi-story fashion shopping mall in Tokyo known as a trendsetting hub for youth and street fashion.
-
D.
Tokyo Solamachi
Tokyo Solamachi is a large shopping, dining, and entertainment complex located at the base of Tokyo Skytree in Tokyo, Japan.
-
E.
Harajuku Lovers
Harajuku Lovers is a Japanese street-style-inspired fashion and accessories brand created by musician and designer Gwen Stefani.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MadeinTYO Triple: [Beach House 3, featuresArtist, MadeinTYO]
Generated description
MadeinTYO is an American rapper and songwriter best known for his breakout hit "Uber Everywhere" and his melodic, laid-back trap style.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MadeinTYO Target entity description: MadeinTYO is an American rapper and songwriter best known for his breakout hit "Uber Everywhere" and his melodic, laid-back trap style.
-
A.
TYO
TYO is the metropolitan airport code representing the Tokyo area’s major airports, primarily Haneda (HND) and Narita (NRT).
-
B.
Harajuku
Harajuku is a vibrant Tokyo district famous for its youth culture, eclectic street fashion, and trendy shopping and entertainment spots.
-
C.
Shibuya 109
Shibuya 109 is a famous multi-story fashion shopping mall in Tokyo known as a trendsetting hub for youth and street fashion.
-
D.
Tokyo Solamachi
Tokyo Solamachi is a large shopping, dining, and entertainment complex located at the base of Tokyo Skytree in Tokyo, Japan.
-
E.
Harajuku Lovers
Harajuku Lovers is a Japanese street-style-inspired fashion and accessories brand created by musician and designer Gwen Stefani.
- F. None of above. chosen
Provenance (5 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf13b2881908a48058a719d3745 |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce8452648190b7392d75eb1ca874 |
completed | May 3, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69f7cf37cd7c81908f4da2495403bc6c |
completed | May 3, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7cfee80a881909de648b20043bf6d |
completed | May 3, 2026, 10:45 p.m. |
Created at: April 9, 2026, 10:16 p.m.