Triple
T13230219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Moss |
E314994
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Janel Moloney |
E99440
|
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: Janel Moloney | Statement: [Donna Moss, portrayedBy, Janel Moloney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janel Moloney Context triple: [Donna Moss, portrayedBy, Janel Moloney]
-
A.
Janel Moloney
chosen
Janel Moloney is an American actress best known for her role as Donna Moss on the political drama television series "The West Wing."
-
B.
Kate Nelligan
Kate Nelligan is a Canadian actress acclaimed for her work in film, television, and theatre, noted for her intense dramatic performances and multiple award nominations.
-
C.
Lisa O'Brien
Lisa O'Brien is the mother of American actor Dylan O'Brien, known for his roles in "Teen Wolf" and "The Maze Runner" film series.
-
D.
Nicole Shanahan
Nicole Shanahan is an American attorney, legal tech entrepreneur, and philanthropist known for founding the patent management company ClearAccessIP and for her high-profile marriage to Google co-founder Sergey Brin.
-
E.
Mary LaRoche
Mary LaRoche was an American actress and singer known for her work in mid-20th-century film, television, and Broadway productions.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d336ae08190bfc118cfbefddf84 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a5a733c819090a6710ab990c38d |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 9, 2026, 9:21 p.m.