Triple
T22503597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3DEXPERIENCE |
E556334
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | BIOVIA |
—
|
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: BIOVIA | Statement: [3DEXPERIENCE, hasComponent, BIOVIA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BIOVIA Context triple: [3DEXPERIENCE, hasComponent, BIOVIA]
-
A.
BIOVIA
chosen
BIOVIA is a Dassault Systèmes software brand focused on scientific informatics and molecular modeling solutions for life sciences, materials science, and chemistry.
-
B.
Sigma-Aldrich Corporation
Sigma-Aldrich Corporation is a major global chemical and life science company known for supplying research, specialty, and fine chemicals to laboratories and industries worldwide.
-
C.
Element Biosciences
Element Biosciences is a biotechnology company that develops next-generation DNA sequencing platforms and technologies for genomic research.
-
D.
Horizon Discovery
Horizon Discovery is a biotechnology company specializing in gene editing and cell-based research tools used for drug discovery and development.
-
E.
Lonza
Lonza is a global Swiss-based life sciences company specializing in pharmaceutical, biotech, and nutrition products and services, particularly in contract development and manufacturing.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5a01888190ba65a05616b63cbe |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.