Triple
T29287521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camille Dreyfus |
E742557
|
entity |
| Predicate | typeOfChemist |
P43012
|
FINISHED |
| Object | organic chemist |
—
|
LITERAL 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: organic chemist | Statement: [Camille Dreyfus, typeOfChemist, organic chemist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfChemist Context triple: [Camille Dreyfus, typeOfChemist, organic chemist]
-
A.
usesChemistry
Indicates that one entity applies or relies on chemistry, chemical methods, or chemical principles in relation to another entity or context.
-
B.
hasNotableChemist
Indicates that an entity is associated with or distinguished by a particular chemist who is notable or prominent in the field of chemistry.
-
C.
commonChemistry
Indicates that two entities share similar or related chemical properties, composition, or behavior.
-
D.
keyChemicalDiscussed
Indicates that a particular chemical substance is a central topic of discussion in a given context or communication.
-
E.
typeOfScientist
chosen
Indicates that one entity is a scientist and the other specifies the kind or specialization of that scientist.
- F. None of above.
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_69f09121ed8c8190b4cb27be3619c262 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
Created at: April 28, 2026, 12:59 p.m.