Triple
T20784906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Scott Connors |
E511602
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Gloria Connors |
—
|
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: Gloria Connors | Statement: [James Scott Connors, mother, Gloria Connors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gloria Connors Context triple: [James Scott Connors, mother, Gloria Connors]
-
A.
Gloria Connors
chosen
Gloria Connors was an American tennis coach best known as the mother and early mentor of tennis champion Jimmy Connors.
-
B.
Gloria Loomis
Gloria Loomis is a literary agent and the wife of the late American screenwriter Walter Bernstein.
-
C.
Gloria Greer
Gloria Greer was an American actress best known for her work in early 20th-century films and for her marriage to film director Alan Crosland.
-
D.
Gloria Swenson
Gloria Swenson is the tough, streetwise former mob moll who becomes an unlikely protector of a young boy in the crime thriller film "Gloria."
-
E.
Gloria Holden
Gloria Holden was a British-born American actress best known for her roles in classic Hollywood films of the 1930s and 1940s, particularly in horror and drama genres.
- 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_69e0b4cac7a48190a715cb3d545df2b4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28b4ce88190a45f1c99b58d18eb |
completed | April 21, 2026, 12:19 a.m. |
Created at: April 16, 2026, 12:38 p.m.