Triple
T9938091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CVS Health |
E194005
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Sidney Goldstein |
E882684
|
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: Sidney Goldstein | Statement: [CVS Health, foundedBy, Sidney Goldstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sidney Goldstein Context triple: [CVS Health, foundedBy, Sidney Goldstein]
-
A.
Stanley Goldstein
chosen
Stanley Goldstein is an American businessman best known as a co-founder and former leader of the CVS pharmacy chain, which grew into CVS Health.
-
B.
Bernard Goldston
Bernard Goldston is an entrepreneur best known as the founder of the American off-price department store chain Marshalls.
-
C.
Sydney Goldstein
Sydney Goldstein was a British mathematician known for his influential work in fluid dynamics and aerodynamics.
-
D.
Bernard Goldstein
Bernard Goldstein is a notable individual whose achievements or prominence have made the surname Goldstein particularly recognized.
-
E.
Gil Goldschein
Gil Goldschein is a television producer and media executive best known for his work on reality TV series, including projects in the Kardashian franchise.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e64760819094f599f158d32f33 |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de21a949508190ad16b061ead5ed24 |
completed | April 14, 2026, 11:14 a.m. |
Created at: March 30, 2026, 8:44 p.m.