Triple
T199793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byron Nelson |
E4077
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nelson |
E1145
|
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: Nelson | Statement: [Byron Nelson, familyName, Nelson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nelson Context triple: [Byron Nelson, familyName, Nelson]
-
A.
Nelson
chosen
Nelson is a common English-language surname borne by numerous notable figures across politics, sports, entertainment, and academia.
-
B.
Douglas
Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
-
C.
Guilfoyle
Guilfoyle is a surname most prominently associated in contemporary American culture with television personality and political figure Kimberly Guilfoyle.
-
D.
Anthony van Diemen
Anthony van Diemen was a 17th-century Dutch colonial administrator best known for expanding Dutch influence in Asia and for lending his name to Van Diemen’s Land, now Tasmania.
-
E.
Cabell
Cabell is a surname of English origin borne by various notable individuals, including American politician Earle Cabell.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3441a5fb08190971136c2ec6e79ee |
completed | Feb. 28, 2026, 7:38 p.m. |
Created at: Feb. 28, 2026, 2:44 a.m.