Triple
T22480648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Ellen Noonan |
E555754
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ellen |
—
|
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: Ellen | Statement: [Margaret Ellen Noonan, givenName, Ellen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ellen Context triple: [Margaret Ellen Noonan, givenName, Ellen]
-
A.
Ellen
Ellen is a fictional character in Ken Follett's World War II-era thriller novel "Night Over Water."
-
B.
Ellen
"Ellen" is an American television sitcom starring Ellen DeGeneres that became especially notable for its groundbreaking coming-out episode in the 1990s.
-
C.
Ellen
chosen
Ellen is a feminine given name of Greek origin, commonly associated with meanings related to light or brightness.
-
D.
Ellen
Ellen is a character in William Morris’s utopian novel "News from Nowhere," representing aspects of the idealized future society depicted in the book.
-
E.
Ellen
Ellen is a central character in Kenneth Lonergan’s play "The Waverly Gallery," navigating the emotional and familial challenges surrounding her grandmother’s decline.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c3836a08190b6f0d88b94cb80a3 |
completed | April 29, 2026, 1:17 a.m. |
Created at: April 16, 2026, 8:49 p.m.