Triple
T8248393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hydra |
E192900
|
entity |
| Predicate | supportsProtocol |
P203
|
FINISHED |
| Object | CVS |
E184314
|
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: CVS | Statement: [Hydra, supportsProtocol, CVS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CVS Context triple: [Hydra, supportsProtocol, CVS]
-
A.
CVS
chosen
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
CVS is the commonly used abbreviation for the Center for Visual Science, a research organization focused on the scientific study of vision.
-
D.
CVS Health
CVS Health is a major American healthcare company that operates a large pharmacy chain and provides health insurance and pharmacy benefit management services.
-
E.
Duane Reade
Duane Reade is a New York City–based chain of neighborhood pharmacy and convenience stores known for its dense urban presence and everyday consumer goods.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78c6b3c48190a3ecebf449766124 |
completed | March 31, 2026, 7:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3530ca148190a28761622d0cf663 |
completed | April 1, 2026, 3:09 p.m. |
Created at: March 30, 2026, 5:48 p.m.