Triple
T3034018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Barksdale |
E82963
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | AT&T Wireless |
E89783
|
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: AT&T Wireless | Statement: [Jim Barksdale, employer, AT&T Wireless]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AT&T Wireless Context triple: [Jim Barksdale, employer, AT&T Wireless]
-
A.
AT&T
chosen
AT&T is a major American telecommunications conglomerate known for providing wireless, internet, and media services nationwide.
-
B.
Verizon
Verizon is a major American telecommunications company providing wireless, internet, and related communication services across the United States and globally.
-
C.
Alltel
Alltel was a major American wireless telecommunications company that provided mobile phone services across numerous U.S. states before being largely acquired by Verizon Wireless.
-
D.
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.
-
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_69ad8b21a62881908ec5dd4fba4a187c |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9af13ce48190bda4f5ca0ffe6285 |
completed | March 8, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1dec30d8081909d6ee691e5e51434 |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3:01 p.m.