Triple
T15339312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Travis Bacon |
E366747
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Sosie Bacon |
E365981
|
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: Sosie Bacon | Statement: [Travis Bacon, sibling, Sosie Bacon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sosie Bacon Context triple: [Travis Bacon, sibling, Sosie Bacon]
-
A.
Sosie Bacon
chosen
Sosie Bacon is an American actress known for roles in film and television, including the horror film "Smile" and the series "Mare of Easttown."
-
B.
Horace Badun
Horace Badun is a bumbling, dim-witted henchman who works for Cruella de Vil in Disney’s 101 Dalmatians franchise.
-
C.
Thane Baker
Thane Baker was an American sprinter and Olympic medalist known for his achievements in the 100 m and 200 m events during the 1950s.
-
D.
Will Bates
Will Bates is a film and television composer known for his atmospheric and suspenseful scores across a range of genre projects.
-
E.
Frank Partos
Frank Partos was a Hungarian-American screenwriter known for his work on notable Hollywood films in the mid-20th century, including influential psychological dramas.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e12eb7c8190944a260aa1aa9156 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01f2ee9c819080fce24ed13a07c7 |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.