Triple
T10416780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Ray Norwood Jr. |
E245537
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object | Sonja Norwood |
E449226
|
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: Sonja Norwood | Statement: [William Ray Norwood Jr., parent, Sonja Norwood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sonja Norwood Context triple: [William Ray Norwood Jr., parent, Sonja Norwood]
-
A.
Sonja Norwood
chosen
Sonja Norwood is an American talent manager and television personality best known for managing the careers of her children, singer-actress Brandy and entertainer Ray J.
-
B.
Marilee Earle
Marilee Earle is an actress best known for her role in the 1958 Western film "Terror in a Texas Town."
-
C.
Linda Nordley
Linda Nordley is a central female character in the 1953 adventure film "Mogambo," portrayed as a refined Englishwoman whose arrival complicates the romantic and emotional dynamics on an African safari.
-
D.
Sonja Hogg
Sonja Hogg is an American women's basketball coach best known for helping build Baylor University's women's program into a national contender.
-
E.
Jane Loring
Jane Loring was a film editor known for her work in early 20th-century American cinema.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea1194e08190a18c3b3002147493 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e2527570819092314ee0a678e53c |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 6, 2026, 12:10 p.m.