Triple
T26294845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | He's All That |
E661385
|
entity |
| Predicate | characterAnnaSawyerPortrayedBy |
P1507
|
FINISHED |
| Object | Rachael Leigh Cook |
—
|
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: Rachael Leigh Cook | Statement: [He's All That, characterAnnaSawyerPortrayedBy, Rachael Leigh Cook]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAnnaSawyerPortrayedBy Context triple: [He's All That, characterAnnaSawyerPortrayedBy, Rachael Leigh Cook]
-
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.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
C.
sonCharacterPortrayedBy
Indicates that a person is the actor who portrays a specific son character in a work of fiction.
-
D.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
E.
leadActressCharacterName
Indicates the name of the character portrayed by the lead actress in a given work.
- 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_69ee812cd48c81908054068f545f0526 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 26, 2026, 10:11 p.m.