Triple
T6804656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John de Mol |
E156272
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Talpa Network |
E620332
|
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: Talpa Network | Statement: [John de Mol, employer, Talpa Network]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talpa Network Context triple: [John de Mol, employer, Talpa Network]
-
A.
Talpa Network
chosen
Talpa Network is a Dutch media company founded by television producer and entrepreneur John de Mol, known for its television, radio, and digital entertainment platforms.
-
B.
Talpa Media
Talpa Media is a Dutch television production company best known for creating international reality and talent show formats such as "The Voice."
-
C.
Talpa Global
Talpa Global is the international distribution and licensing arm of Talpa Media, responsible for bringing its television formats and content to markets worldwide.
-
D.
Talpa Productions
Talpa Productions is a Dutch television production company best known for creating internationally successful reality and talent show formats.
-
E.
Gulmakai Network
The Gulmakai Network is a Malala Fund initiative that supports and connects local education advocates and organizations working to advance girls’ secondary education in regions where it is most at risk.
- 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_69c68826e6a48190a3d220b541e639de |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ea459c819095388218d53c250a |
completed | March 27, 2026, 6:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723d525bc8190aaf2390d690dc6a6 |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 27, 2026, 2:16 p.m.