Triple
T14158654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia Engel |
E350877
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Georgia Engel |
E350877
|
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: Georgia Engel | Statement: [Georgia Engel, name, Georgia Engel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgia Engel Context triple: [Georgia Engel, name, Georgia Engel]
-
A.
Georgia Engel
chosen
Georgia Engel was an American actress best known for her soft-spoken, sweetly quirky roles in television comedies such as "The Mary Tyler Moore Show" and "Everybody Loves Raymond."
-
B.
Eve McClure
Eve McClure was an American artist and the third wife of writer Henry Miller, known for her influence on his life and work during the 1940s.
-
C.
Didi Conn
Didi Conn is an American actress best known for her role as the bubbly, high-voiced Frenchy in the classic film musical "Grease."
-
D.
Wynonie Harris
Wynonie Harris was an influential American blues and R&B singer whose energetic performances and hit records in the 1940s and 1950s helped shape the development of rock and roll.
-
E.
Molly Messick
Molly Messick is an American audio producer and journalist known for her work in public radio and podcasting.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61377de48190a3470d28f0edd34a |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7ef4d80819098d210503f5d22e9 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 12:58 a.m.