Triple
T4890465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirk Stikker |
E109546
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dirk Stikker |
E109546
|
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: Dirk Stikker | Statement: [Dirk Stikker, name, Dirk Stikker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dirk Stikker Context triple: [Dirk Stikker, name, Dirk Stikker]
-
A.
Dirk Stikker
chosen
Dirk Stikker was a Dutch banker, politician, and diplomat who served as NATO Secretary General and played a key role in post–World War II European politics.
-
B.
Roel van Velzen
Roel van Velzen is a Dutch singer-songwriter, musician, and television personality best known as the frontman of the pop-rock band VanVelzen and as a coach on The Voice of Holland.
-
C.
Peter van Dam
Peter van Dam is a notable individual whose surname "van Dam" is recognized as being borne by him.
-
D.
Dirk Frimout
Dirk Frimout is a Belgian astrophysicist and astronaut who became the first Belgian in space during a Space Shuttle mission.
-
E.
Sander Dieleman
Sander Dieleman is a machine learning researcher known for his influential work in deep learning for audio and music, including contributions to models such as WaveNet.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e07ca10819083f80f12374544b1 |
completed | March 20, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be681a3d7881908120dc642af3f58a |
completed | March 21, 2026, 9:42 a.m. |
Created at: March 20, 2026, 1:28 p.m.