Triple
T23262598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Never Liked You |
E582052
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | K Major |
E1019003
|
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: K Major | Statement: [I Never Liked You, producer, K Major]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K Major Context triple: [I Never Liked You, producer, K Major]
-
A.
K-Major
chosen
K-Major is an American songwriter and record producer known for his work in contemporary R&B and hip-hop.
-
B.
Korem
Korem is a town in the Tigray Region of northern Ethiopia, known historically for its role in the 1980s famine and associated relief efforts.
-
C.
Mitterie
Mitterie is a metro station on the Lille Metro network in northern France, serving the Line 2 route.
-
D.
Großer Kaserer
Großer Kaserer is a prominent glacier-covered mountain peak in the Zillertal Alps on the Austria–Italy border, popular for alpine skiing and mountaineering.
-
E.
Korgeneral
Korgeneral is a high-ranking general officer position in the Turkish Armed Forces, typically equivalent to a lieutenant general in many NATO militaries.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194caaf208190931923744692180d |
completed | April 29, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3f7050388190a0848037c96049c0 |
completed | May 19, 2026, 10:46 a.m. |
Created at: April 17, 2026, 4:11 p.m.