Triple
T12382191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aye |
E295770
|
entity |
| Predicate | recordLabel |
P1500
|
FINISHED |
| Object | HKN Music |
E974425
|
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: HKN Music | Statement: [Aye, recordLabel, HKN Music]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HKN Music Context triple: [Aye, recordLabel, HKN Music]
-
A.
HKN Music
chosen
HKN Music is a Nigerian record label and music collective known for nurturing Afrobeats artists and collaborating closely with Davido and his musical affiliates.
-
B.
HKNW
HKNW is the ICAO airport code assigned to Wilson Airport in Nairobi, Kenya.
-
C.
HKN
HKN is the station code for Hankou Railway Station, a major rail transport hub in Wuhan, China.
-
D.
Kennis Music
Kennis Music is a prominent Nigerian record label known for shaping the country’s contemporary music scene and launching the careers of several major Afrobeats artists.
-
E.
KPM Music
KPM Music is a renowned production music library and label known for its extensive catalog of high-quality stock and library music used in film, television, and other media.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbb3a2481908c2fcb5e6488eb3c |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f634760210819080bc0261aa059132 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.