Triple
T14302692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Pet Sematary" |
E354607
|
entity |
| Predicate | coverArtist |
P184
|
FINISHED |
| Object | Linda Fennimore |
—
|
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: Linda Fennimore | Statement: ["Pet Sematary", coverArtist, Linda Fennimore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Fennimore Context triple: ["Pet Sematary", coverArtist, Linda Fennimore]
-
A.
Linda Fennimore
chosen
Linda Fennimore is an artist best known for creating the cover art for Stephen King’s horror novel "Pet Sematary."
-
B.
Linda Nordley
Linda Nordley is a central female character in the 1953 adventure film "Mogambo," portrayed as a refined Englishwoman whose arrival complicates the romantic and emotional dynamics on an African safari.
-
C.
Jane Loring
Jane Loring was a film editor known for her work in early 20th-century American cinema.
-
D.
Rachel Greer
Rachel Greer is a professional known for her expertise in Amazon marketplace compliance, product safety, and e-commerce consulting.
-
E.
Eileen Morrow
Eileen Morrow is a person notable enough to be recognized as a significant bearer of the surname Morrow.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717fc2348190bb6ba3109bd2871f |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:12 a.m.