Triple
T20656289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byron Leftwich |
E507633
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Byron |
—
|
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: Byron | Statement: [Byron Leftwich, givenName, Byron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Byron Context triple: [Byron Leftwich, givenName, Byron]
-
A.
Byron
Byron is the middle name of American professional golfer Byron Nelson, one of the sport’s early 20th-century legends.
-
B.
Byron
Byron is a small city in central Georgia, United States, known for its historic downtown and location along major transportation routes near Macon.
-
C.
Byron
Byron is the given first name of Ban Johnson, the influential early 20th-century American baseball executive who served as the founding president of the American League.
-
D.
Byron
chosen
Byron is a masculine given name of Old English origin, commonly associated with the English Romantic poet Lord Byron.
-
E.
Byron
Byron is a surname of English origin borne by various notable individuals across fields such as literature, politics, and the arts.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2ed48308190b9350a323b9a7952 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:43 a.m.