Triple
T32510587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Target pharmacy and clinic businesses |
E830918
|
entity |
| Predicate | customersServed |
P9906
|
FINISHED |
| Object | Target shoppers |
—
|
LITERAL 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: Target shoppers | Statement: [Target pharmacy and clinic businesses, customersServed, Target shoppers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: customersServed Context triple: [Target pharmacy and clinic businesses, customersServed, Target shoppers]
-
A.
hasCustomers
Indicates that an entity maintains a business relationship in which other entities purchase or receive its goods or services as customers.
-
B.
exportCustomersCountEstimate
Indicates an estimated number of customers included in an export operation.
-
C.
servesCustomer
chosen
Indicates that one entity provides service, assistance, or products to another entity in the role of a customer.
-
D.
trafficServed
Indicates that a system, component, or entity handles, processes, or carries a specified amount or type of traffic (e.g., network, data, or user requests).
-
E.
initialCustomers
Indicates that the referenced entities are customers present or involved at the starting point of a process, period, or system.
- 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_69f6c497459081908caefb70f03ee38d |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1 a.m.