Triple
T13829019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigo |
E332333
|
entity |
| Predicate | designedFor |
P98
|
FINISHED |
| Object | Human Made |
E1064557
|
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: Human Made | Statement: [Nigo, designedFor, Human Made]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Human Made Context triple: [Nigo, designedFor, Human Made]
-
A.
Human Made
chosen
Human Made is a Japanese streetwear brand known for its vintage Americana-inspired designs and close association with creator Nigo.
-
B.
Made
Made is a town in the Dutch province of North Brabant, known as one of the population centers within the municipality of Drimmelen.
-
C.
The People Machine
The People Machine is a book by journalist Robert MacNeil that explores the influence of television and mass media on politics and public perception.
-
D.
The Human Factor
The Human Factor is a biographical sports drama film about Nelson Mandela’s use of rugby to help unite post-apartheid South Africa, adapted from John Carlin’s book "Playing the Enemy."
-
E.
Man and Machine
"Man and Machine" is a key chapter in Peter Thiel’s book "Zero to One" that explores how humans and computers can best complement each other in creating innovative, future-defining technologies.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02970df88190a1bf35dffd131d9d |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0eb7f44819087b1d24e4235a972 |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 10:13 p.m.