Triple
T16169622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCann Erickson |
E392398
|
entity |
| Predicate | hasClient |
P734
|
FINISHED |
| Object | Verizon |
E6433
|
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: Verizon | Statement: [McCann Erickson, hasClient, Verizon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verizon Context triple: [McCann Erickson, hasClient, Verizon]
-
A.
Verizon
chosen
Verizon is a major American telecommunications company providing wireless, internet, and related communication services across the United States and globally.
-
B.
AT&T
AT&T is a major American telecommunications conglomerate known for providing wireless, internet, and media services nationwide.
-
C.
T-Mobile US
T-Mobile US is a major American wireless network operator known for its nationwide mobile phone services and aggressive “Un-carrier” marketing strategy.
-
D.
Rogers Wireless
Rogers Wireless is one of Canada’s largest mobile network operators, providing nationwide wireless voice, data, and related telecommunications services.
-
E.
U.S. Cellular
U.S. Cellular is a regional American wireless telecommunications provider offering mobile phone and data services, primarily in the Midwest and rural areas of the United States.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb5e6d881908749683091afa90c |
completed | April 17, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017a7223c81909f04144bdffb22ff |
completed | May 10, 2026, 5:29 a.m. |
Created at: April 10, 2026, 5:02 a.m.