Triple
T20074619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Center for Visual Science |
E499827
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | CVS |
—
|
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: CVS | Statement: [Center for Visual Science, abbreviation, CVS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CVS Context triple: [Center for Visual Science, abbreviation, CVS]
-
A.
CVS
CVS (Concurrent Versions System) is an early, widely used open-source version control system that manages changes to source code in collaborative software development.
-
B.
CVS
CVS is the IATA airport code for Cannon Air Force Base, a United States Air Force installation near Clovis, New Mexico.
-
C.
CVS
chosen
CVS is the commonly used abbreviation for the Center for Visual Science, a research organization focused on the scientific study of vision.
-
D.
CVS
CVS is the station code for Charlottesville station, an Amtrak rail station serving Charlottesville, Virginia.
-
E.
CVS Pharmacy
CVS Pharmacy is a major American retail pharmacy chain offering prescription medications, health and wellness products, and general merchandise.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643ab0448190ab18d013b72aaf32 |
completed | April 20, 2026, 5:36 p.m. |
Created at: April 11, 2026, 3:40 p.m.