Triple
T921649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Szegedy |
E19896
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object | Vincent Vanhoucke |
E48390
|
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: Vincent Vanhoucke | Statement: [Christian Szegedy, coAuthor, Vincent Vanhoucke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vincent Vanhoucke Context triple: [Christian Szegedy, coAuthor, Vincent Vanhoucke]
-
A.
Vincent Vanhoucke
chosen
Vincent Vanhoucke is a prominent machine learning researcher and engineering leader known for his influential work in deep learning and artificial intelligence at Google.
-
B.
Theo Francken
Theo Francken is a Belgian politician known for his hardline stance on immigration and prominent role within the New Flemish Alliance (N-VA).
-
C.
Jan van der Heyden
Jan van der Heyden was a 17th-century Dutch painter and inventor renowned for his detailed cityscapes and pioneering improvements in firefighting technology and street lighting.
-
D.
Jan van de Cappelle
Jan van de Cappelle was a 17th-century Dutch Golden Age painter and etcher renowned for his serene marine and winter landscape scenes.
-
E.
Cornelis de Man
Cornelis de Man was a Dutch Golden Age painter known for his detailed genre scenes, portraits, and interiors, active primarily in Delft.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b313cb908190ad78b3a54e4f2eb7 |
completed | March 1, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2d3cb588190882a480c18147384 |
completed | March 7, 2026, 10:12 p.m. |
Created at: March 1, 2026, 7:40 p.m.