Triple
T14275510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motsi Mabuse |
E353904
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | RTL |
E818081
|
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: RTL | Statement: [Motsi Mabuse, employer, RTL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RTL Context triple: [Motsi Mabuse, employer, RTL]
-
A.
RTL
RTL is the public transit agency serving the city of Longueuil and surrounding areas in the Greater Montreal region of Quebec, Canada.
-
B.
RTL
chosen
RTL is a major German commercial television channel known for broadcasting popular entertainment, drama series, and reality programming.
-
C.
RTL 7
RTL 7 is a Dutch commercial television channel known for broadcasting sports, action series, and male-oriented entertainment programming.
-
D.
RL
RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
-
E.
RL
RL is an American R&B singer best known as a member of the group Next and for his smooth vocal contributions to late-1990s and early-2000s R&B hits.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6582f5308190969f4cfd724d9139 |
completed | April 14, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd326d35808190bbf3f6bbc50554f4 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:10 a.m.