Triple
T11210347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ENS Paris |
E265287
|
entity |
| Predicate | hasAlumni |
P51
|
FINISHED |
| Object | Louis Pasteur |
E29652
|
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: Louis Pasteur | Statement: [ENS Paris, hasAlumni, Louis Pasteur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Louis Pasteur Context triple: [ENS Paris, hasAlumni, Louis Pasteur]
-
A.
Louis Pasteur
chosen
Louis Pasteur was a pioneering French chemist and microbiologist whose work on germ theory, vaccination, and pasteurization revolutionized medicine and public health.
-
B.
Jean-Baptiste Pasteur
Jean-Baptiste Pasteur was one of the children of the renowned French chemist and microbiologist Louis Pasteur.
-
C.
Camille Pasteur
Camille Pasteur was one of the children of the renowned French chemist and microbiologist Louis Pasteur.
-
D.
Alexandre Yersin
Alexandre Yersin was a Swiss-French physician and bacteriologist best known for identifying the plague bacillus (Yersinia pestis) and contributing significantly to infectious disease research in the late 19th century.
-
E.
Émile Roux
Émile Roux was a French physician, bacteriologist, and pioneer of immunology who played a key role in developing vaccines and antitoxins, notably for diphtheria.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d6f5d4819086dcb776a0d469e8 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e49747ec288190bc3e826b6de7f6f2 |
completed | April 19, 2026, 8:50 a.m. |
Created at: April 8, 2026, 9:30 p.m.