Triple
T18806702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theranos |
E459893
|
entity |
| Predicate | majorPartner |
P34923
|
FINISHED |
| Object | Safeway |
—
|
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: Safeway | Statement: [Theranos, majorPartner, Safeway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Safeway Context triple: [Theranos, majorPartner, Safeway]
-
A.
Safeway
chosen
Safeway is a major American supermarket chain offering groceries, household goods, and pharmacy services across numerous locations.
-
B.
Kroger
Kroger is one of the largest supermarket and retail grocery chains in the United States, operating thousands of stores under various banners nationwide.
-
C.
Meijer
Meijer is a Dutch-origin surname borne by numerous individuals, including notable figures in business, politics, and the arts.
-
D.
Albertsons
Albertsons is a major American supermarket and grocery retail chain operator with stores across numerous states under various regional banners.
-
E.
First National Supermarket
First National Supermarket is a regional grocery store chain where employees like Tami-Lynn work in various retail and customer service roles.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3d7f8d08190a3e02fab6dc40bb5 |
completed | April 20, 2026, 3:56 a.m. |
Created at: April 10, 2026, 11:53 a.m.