Triple
T14587158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harris Teeter |
E342345
|
entity |
| Predicate | parentOrganization |
P254
|
FINISHED |
| Object | Kroger |
E68030
|
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: Kroger | Statement: [Harris Teeter, parentOrganization, Kroger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kroger Context triple: [Harris Teeter, parentOrganization, Kroger]
-
A.
Kroger
chosen
Kroger is one of the largest supermarket and retail grocery chains in the United States, operating thousands of stores under various banners nationwide.
-
B.
Safeway
Safeway is a major American supermarket chain offering groceries, household goods, and pharmacy services across numerous locations.
-
C.
Meijer
Meijer is a Dutch-origin surname borne by numerous individuals, including notable figures in business, politics, and the arts.
-
D.
Publix
Publix is a major employee-owned American supermarket chain based in the Southeastern United States.
-
E.
Dollar General
Dollar General is a major American discount retail chain known for its widespread network of small-format stores offering low-priced household goods and everyday essentials.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb421bb308190a457425429ef6aa5 |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f21a97c819082b59b343ef337ec |
completed | May 9, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:24 a.m.