Triple
T10794039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eileen Ryan |
E254657
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Eileen Ryan |
E254657
|
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: Eileen Ryan | Statement: [Eileen Ryan, name, Eileen Ryan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eileen Ryan Context triple: [Eileen Ryan, name, Eileen Ryan]
-
A.
Eileen Ryan
chosen
Eileen Ryan was an American actress known for her character roles in film and television and as the mother of actor and director Sean Penn.
-
B.
Deirdre Flynn
Deirdre Flynn is the daughter of famed Hollywood swashbuckling actor Errol Flynn.
-
C.
Patricia O'Brien
Patricia O'Brien is an American writer and journalist known for her collaborations with Pulitzer Prize–winning columnist Ellen Goodman and for her own works of fiction and non-fiction.
-
D.
Judy Ryan
Judy Ryan is a sports administrator who has served as the athletic director for the University of Maine's Maine Black Bears athletic program.
-
E.
Mary McLaglen
Mary McLaglen is a film producer known for her work on major Hollywood movies, including romantic comedies and action films.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732f878648190be5e25c56a7511cf |
completed | April 9, 2026, 5:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e15499158481908391f411420b19fc |
completed | April 16, 2026, 9:28 p.m. |
Created at: April 8, 2026, 9:17 p.m.