Triple
T14087551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose Nylund |
E339035
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Susan Harris |
E289200
|
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: Susan Harris | Statement: [Rose Nylund, createdBy, Susan Harris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susan Harris Context triple: [Rose Nylund, createdBy, Susan Harris]
-
A.
Susan Harris
chosen
Susan Harris is an American television writer and producer best known for creating the acclaimed sitcom "The Golden Girls."
-
B.
Susan Harrison
Susan Harrison was an American actress best known for her memorable role in the classic "The Twilight Zone" episode "Five Characters in Search of an Exit."
-
C.
Rebecca Harris
Rebecca Harris is a fictional character portrayed by Jennifer Carpenter, best known as the determined FBI agent in the television series "Limitless."
-
D.
Ann Hearn
Ann Hearn is an American actress known for her supporting roles in film and television, including an appearance in the legal drama "The Accused."
-
E.
Susan Haggett
Susan Haggett is a character in the play "The Late Christopher Bean," typically portrayed as a young woman whose relationships and reactions help reveal the impact of the deceased artist’s legacy on those around him.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ee1ce88819091c983286289337e |
completed | April 14, 2026, 3:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64e47f1c8190a4ad09bc96d35b69 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 9, 2026, 10:21 p.m.