Triple
T3898694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come and Get It |
E90433
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Joel McCrea |
E159573
|
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: Joel McCrea | Statement: [Come and Get It, starring, Joel McCrea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joel McCrea Context triple: [Come and Get It, starring, Joel McCrea]
-
A.
Joel McCrea
chosen
Joel McCrea was an American film actor best known for his leading roles in classic Hollywood Westerns and comedies from the 1930s through the 1950s.
-
B.
Randolph Scott
Randolph Scott was a prominent American film actor best known for his roles in Westerns during the 1930s–1950s.
-
C.
Robert Cummings
Robert Cummings was an American film and television actor best known for his roles in comedies and thrillers during Hollywood’s Golden Age.
-
D.
Bradford Dillman
Bradford Dillman was an American actor known for his work in film, television, and theater from the 1950s through the 1990s, often portraying complex or authoritative characters.
-
E.
Dana Andrews
Dana Andrews was a prominent American film actor of the 1940s and 1950s, best known for his leading roles in classics such as "Laura" and "The Best Years of Our Lives."
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecefa3608190a7a20ed6df6a64b2 |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b53fe99ccc8190849ffe819a4bfd8f |
completed | March 14, 2026, 11 a.m. |
Created at: March 9, 2026, 3:21 p.m.