Triple
T19868215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legally Blonde |
E477445
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Matthew Davis |
—
|
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: Matthew Davis | Statement: [Legally Blonde, starring, Matthew Davis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Davis Context triple: [Legally Blonde, starring, Matthew Davis]
-
A.
Matthew Davis
chosen
Matthew Davis is an American actor best known for his role as Alaric Saltzman on the supernatural drama television series "The Vampire Diaries."
-
B.
Jonathan Dancy
Jonathan Dancy is a British moral philosopher best known for his work on moral particularism and contributions to contemporary ethical theory.
-
C.
Clark Duke
Clark Duke is an American actor, comedian, and filmmaker known for roles in projects like "Hot Tub Time Machine," "The Office," and "Kick-Ass."
-
D.
Daniel Henney
Daniel Henney is an American actor and model known for his roles in films and television series such as "Big Hero 6," "Criminal Minds," and "The Wheel of Time."
-
E.
Jay Levey
Jay Levey is an American film and music video director best known for directing "Weird Al" Yankovic’s 1989 cult comedy film *UHF* and many of the musician’s iconic videos.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a168288190a2fbb735d1fd30a8 |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.