Triple
T18629594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Guez |
E455377
|
entity |
| Predicate | coAuthorWith |
P398
|
FINISHED |
| Object | Hado van Hasselt |
—
|
NE NERFINISHED |
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: Hado van Hasselt | Statement: [Arthur Guez, coAuthorWith, Hado van Hasselt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hado van Hasselt Context triple: [Arthur Guez, coAuthorWith, Hado van Hasselt]
-
A.
Hado van Hasselt
chosen
Hado van Hasselt is a researcher in reinforcement learning best known for pioneering methods such as Double Q-learning and Dueling DQN that address overestimation bias and improve deep RL performance.
-
B.
Maarten ’t Hart
Maarten ’t Hart is a Dutch writer and biologist known for his psychologically rich novels and essays, often drawing on his strict religious upbringing and love of classical music.
-
C.
An D’Huys
An D’Huys is a costume designer known for her work on the stage adaptation of "All About Eve" and other prominent theatre and film productions.
-
D.
Jan Kempdorp
Jan Kempdorp is a small agricultural and service town in South Africa’s Northern Cape province.
-
E.
Theo Heemskerk
Theo Heemskerk was a Dutch politician who served as Prime Minister of the Netherlands in the early 20th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54f06f4a081909b64f33814577488 |
completed | April 19, 2026, 9:54 p.m. |
Created at: April 10, 2026, 11:46 a.m.