Triple
T500252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hanks |
E10383
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Green Mile |
E37262
|
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: The Green Mile | Statement: [Tom Hanks, notableWork, The Green Mile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Green Mile Context triple: [Tom Hanks, notableWork, The Green Mile]
-
A.
The Green Mile
chosen
The Green Mile is a serialized novel by Stephen King that blends supernatural elements with a poignant death-row drama set in a 1930s Southern prison.
-
B.
The Executioner’s Song
The Executioner’s Song is a Pulitzer Prize–winning nonfiction novel by Norman Mailer that chronicles the life, crimes, and execution of convicted murderer Gary Gilmore.
-
C.
The Big House
The Big House is the massive on-campus football stadium at the University of Michigan in Ann Arbor, renowned as one of the largest stadiums in the world.
-
D.
The Stand
The Stand is a post-apocalyptic horror novel by Stephen King that follows survivors of a devastating plague as they become embroiled in an epic battle between good and evil.
-
E.
Sophie's Choice
Sophie's Choice is a 1982 drama film, based on William Styron's novel, that follows a Holocaust survivor's harrowing past and present in postwar Brooklyn.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f13096248190a622a58dcf540b00 |
completed | Feb. 28, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a48543f1948190b710628bf53cdf01 |
completed | March 1, 2026, 6:28 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.