Triple
T20207667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Graham |
E493397
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Graham |
—
|
NE NERFINISHED |
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: Graham | Statement: [Fred Graham, familyName, Graham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Graham Context triple: [Fred Graham, familyName, Graham]
-
A.
Graham
Graham is the surname of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics empire.
-
B.
Graham
Graham is a small unincorporated community located in Nodaway County, Missouri, United States.
-
C.
Graham
chosen
Graham is a masculine given name of English origin, historically derived from a surname and commonly used in English-speaking countries.
-
D.
Graham
Graham is the married surname of Magdalen Carnegie, a member of the Scottish noble Carnegie family.
-
E.
Grahams
Grahams are a classification of Scottish mountains between 2,000 and 2,499 feet (610–762 m) in height with a prominence of at least 150 meters, popular among hillwalkers and peak-baggers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d934f808190bbfeb96f5bf2dfb9 |
completed | April 20, 2026, 6:16 p.m. |
Created at: April 11, 2026, 11:38 p.m.