Triple
T17202858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erika van Thiel |
E417521
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Erika van Thiel |
E417521
|
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: Erika van Thiel | Statement: [Erika van Thiel, name, Erika van Thiel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erika van Thiel Context triple: [Erika van Thiel, name, Erika van Thiel]
-
A.
Erika van Thiel
chosen
Erika van Thiel is best known as the wife of Dutch trance DJ and record producer Armin van Buuren.
-
B.
Astrid Nienhuis
Astrid Nienhuis is a Dutch politician who serves as the mayor of the municipality of Heemstede in the Netherlands.
-
C.
Diana Van der Vlis
Diana Van der Vlis was an American actress known for her work in film and television during the 1960s and 1970s.
-
D.
Lida Scholten
Lida Scholten is a Dutch art patron and co-founder of the Museum Beelden aan Zee in The Hague, known for her support of modern and contemporary sculpture.
-
E.
Thekla Reuten
Thekla Reuten is a Dutch actress known for her roles in international films and television series, including English-language productions.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42db11fc881908291bf29cc740e09 |
completed | April 19, 2026, 1:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170e9d4308190a7c97da472d5e4b7 |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:38 a.m.