Triple
T28665609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aloha (2015 film) |
E725578
|
entity |
| Predicate | Tracy Woodside portrayedBy |
P1507
|
FINISHED |
| Object | Rachel McAdams |
—
|
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: Rachel McAdams | Statement: [Aloha (2015 film), Tracy Woodside portrayedBy, Rachel McAdams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Tracy Woodside portrayedBy Context triple: [Aloha (2015 film), Tracy Woodside portrayedBy, Rachel McAdams]
-
A.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
B.
portrayedBySpouseOf
Indicates that something is portrayed or depicted by the spouse of a given entity.
-
C.
portrayedByInSpinOff
Indicates that an entity is portrayed by a particular actor specifically in a spin-off production related to the original work.
-
D.
portrayedByAlsoKnownFor
Indicates that an entity is portrayed by a person who is also notably known for another specific role or work.
-
E.
supportingCharacterPortrayedBy
Indicates that a supporting (non-leading) character in a work is portrayed or acted by a specific performer.
- F. None of above.
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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 5:01 a.m.