Triple
T32510586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Target pharmacy and clinic businesses |
E830918
|
entity |
| Predicate | transitionAgreementWith |
P89484
|
FINISHED |
| Object | CVS Health |
—
|
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 Health | Statement: [Target pharmacy and clinic businesses, transitionAgreementWith, CVS Health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transitionAgreementWith Context triple: [Target pharmacy and clinic businesses, transitionAgreementWith, CVS Health]
-
A.
transferAgreement
chosen
Indicates a formal arrangement in which ownership, rights, or responsibilities are transferred from one party to another.
-
B.
transition
Indicates a change of state or condition from one form, phase, or situation to another.
-
C.
transitionIssue
Indicates a problem or complication that arises during the process of moving from one state, phase, or condition to another.
-
D.
transitionUse
Indicates a relationship where one state, condition, or resource is used as part of moving or changing into another state, condition, or resource.
-
E.
transitionNote
Indicates a note or annotation that describes or qualifies a change, shift, or transition from one state, condition, or context to another.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feafa1ba0081909013800b85a9f613 |
completed | May 9, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69feae58d62c81909d031f3df8992883 |
completed | May 9, 2026, 3:47 a.m. |
Created at: May 1, 2026, 1 a.m.