Triple
T19108415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Priscilla Lane as Jean Sherman |
E467720
|
entity |
| Predicate | coStarsWith |
P14987
|
FINISHED |
| Object | Jeffrey Lynn |
—
|
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: Jeffrey Lynn | Statement: [Priscilla Lane as Jean Sherman, coStarsWith, Jeffrey Lynn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Lynn Context triple: [Priscilla Lane as Jean Sherman, coStarsWith, Jeffrey Lynn]
-
A.
Jeffrey Lynn
chosen
Jeffrey Lynn was an American film and stage actor best known for his roles in 1930s and 1940s Hollywood dramas and romances.
-
B.
Jeffrey Winston
Jeffrey Winston is known as the former husband of American actress Debbi Morgan.
-
C.
Jeffrey Byron
Jeffrey Byron is an American actor known for his work in film and television since the 1960s, including roles in genre and action productions.
-
D.
Jeffrey Heath
Jeffrey Heath is a linguist renowned for his extensive fieldwork and documentation of Dogon and other African languages.
-
E.
Jeffrey Hayden
Jeffrey Hayden was an American television and film director known for his extensive work in mid-20th-century TV dramas and variety shows.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e391f00c8190881a5977dd3728ed |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:04 p.m.