Triple
T7437885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carol Pewterschmidt |
E171664
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Julie Hagerty |
E449197
|
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: Julie Hagerty | Statement: [Carol Pewterschmidt, portrayedBy, Julie Hagerty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julie Hagerty Context triple: [Carol Pewterschmidt, portrayedBy, Julie Hagerty]
-
A.
Julie Hagerty
chosen
Julie Hagerty is an American actress and former model best known for her comedic roles in films such as "Airplane!" and "What About Bob?".
-
B.
Julie Ferguson
Julie Ferguson is the wife of the late American actor and comedian Charles Grodin.
-
C.
Julie Leonard
Julie Leonard was the wife of American film director Norman Taurog, known for her connection to his long career in Hollywood.
-
D.
Janet Healy
Janet Healy is a film producer known for her work on animated features, including the 2012 adaptation of Dr. Seuss's "The Lorax."
-
E.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf4205d7a08190839c10bdfc476d9f |
completed | April 3, 2026, 4:28 a.m. |
Created at: March 27, 2026, 3:13 p.m.