Triple
T28665607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aloha (2015 film) |
E725578
|
entity |
| Predicate | Allison Ng portrayedBy |
P1507
|
FINISHED |
| Object | Emma Stone |
—
|
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: Emma Stone | Statement: [Aloha (2015 film), Allison Ng portrayedBy, Emma Stone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Allison Ng portrayedBy Context triple: [Aloha (2015 film), Allison Ng portrayedBy, Emma Stone]
-
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.
portrayedByInSpinOff
Indicates that an entity is portrayed by a particular actor specifically in a spin-off production related to the original work.
-
C.
portrayedByInSequel
Indicates that an entity is portrayed by a particular actor or performer specifically in a sequel work (e.g., a sequel film, series, or game).
-
D.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
E.
portrayedInOriginalProductionBy
Indicates that an entity (such as a role or character) was first brought to life or performed in the original production 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.