Triple
T4781267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owen Robertson Cheatham |
E106169
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Georgia-Pacific |
E14067
|
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: Georgia-Pacific | Statement: [Owen Robertson Cheatham, employer, Georgia-Pacific]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgia-Pacific Context triple: [Owen Robertson Cheatham, employer, Georgia-Pacific]
-
A.
Georgia-Pacific
chosen
Georgia-Pacific is a major American pulp and paper company known for producing tissue, packaging, building products, and related chemicals.
-
B.
Weyerhaeuser Company
Weyerhaeuser Company is a major American timberland and forest products company, historically one of the world’s largest private owners of softwood timber.
-
C.
International Paper
International Paper is a leading global producer of renewable fiber-based packaging, pulp, and paper products.
-
D.
Crown Zellerbach Corporation
Crown Zellerbach Corporation was a major American pulp and paper company that grew into one of the largest forest products and packaging firms in the United States during the 20th century.
-
E.
UPM
UPM is the Polytechnic University of Madrid, a leading Spanish public university specializing in engineering, architecture, and technology.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65aa577c81909ec1b94e47810169 |
completed | March 20, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43d371b081908142e6d66780e0f0 |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:21 p.m.