Triple
T15681475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phil Connors |
E377585
|
entity |
| Predicate | befriends |
P39937
|
FINISHED |
| Object | Ned Ryerson |
E296003
|
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: Ned Ryerson | Statement: [Phil Connors, befriends, Ned Ryerson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ned Ryerson Context triple: [Phil Connors, befriends, Ned Ryerson]
-
A.
Ned Ryerson
chosen
Ned Ryerson is the overly enthusiastic insurance salesman and former classmate who repeatedly accosts Phil Connors in the film "Groundhog Day."
-
B.
Ned Leeds
Ned Leeds is Peter Parker’s best friend and comic-relief sidekick in the Marvel Cinematic Universe, known for his enthusiastic support of Spider-Man and his humorous, nerdy personality.
-
C.
Kent Rogers
Kent Rogers was an American voice actor best known for his work in classic Warner Bros. cartoons during the 1940s.
-
D.
Dale Jennings
Dale Jennings is a central fictional television news reporter character in the Australian drama series "The Newsreader."
-
E.
Sam O'Steen
Sam O'Steen was an acclaimed American film editor best known for his work on influential films such as "The Graduate," "Chinatown," and "Cool Hand Luke."
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f306a1c8190a819541a3cc51f5a |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee2a33c81908fcd120ca670b309 |
completed | May 9, 2026, 5:29 p.m. |
Created at: April 10, 2026, 4:16 a.m.