Triple
T10668881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evan Bogart |
E251431
|
entity |
| Predicate | hasWorkedWith |
P9615
|
FINISHED |
| Object | MKTO |
E856494
|
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: MKTO | Statement: [Evan Bogart, hasWorkedWith, MKTO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MKTO Context triple: [Evan Bogart, hasWorkedWith, MKTO]
-
A.
MKTO
chosen
MKTO is an American pop-rap duo best known for their hit single "Classic" and their blend of catchy pop hooks with hip-hop influences.
-
B.
MKT
MKT was the reporting mark and common abbreviation for the Missouri–Kansas–Texas Railroad, a major regional railroad that served the south-central United States.
-
C.
MKG
MKG is the three-letter IATA airport code for Muskegon County Airport in Muskegon, Michigan, USA.
-
D.
ARKET
ARKET is a modern, minimalist lifestyle brand offering clothing, accessories, and homeware under the H&M Group.
-
E.
MART
MART is a prominent modern and contemporary art museum in Rovereto, Italy, renowned for its extensive collections and striking contemporary architecture.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f861513881909b44c711371086b7 |
completed | April 9, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a9ceea08190944354d127f2c73b |
completed | April 10, 2026, 10:33 p.m. |
Created at: April 8, 2026, 9:09 p.m.