Triple
T22428084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noah Jupe |
E554424
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Wonder |
—
|
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: Wonder | Statement: [Noah Jupe, notableWork, Wonder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wonder Context triple: [Noah Jupe, notableWork, Wonder]
-
A.
Wonder
chosen
Wonder is a 2017 drama film about a boy with a facial difference navigating school and family life, based on R.J. Palacio’s novel of the same name.
-
B.
Wonder
"Wonder" is a pop studio album by Canadian singer-songwriter Shawn Mendes that showcases his introspective lyrics and expansive, atmospheric production.
-
C.
Wonder
"Wonder" is a 2013 hit single by British producer Naughty Boy featuring Emeli Sandé, known for its uplifting lyrics and soulful, anthemic sound.
-
D.
The Wonder
The Wonder is a psychological period drama film in which Florence Pugh plays an English nurse sent to investigate a young Irish girl who appears to survive without eating.
-
E.
Wonder (II)
Wonder (II) is a track from the album "Laughing Matter" by the American indie rock band Wand.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2f054c819093fbe173c8a4a544 |
completed | April 29, 2026, 1:09 a.m. |
Created at: April 16, 2026, 8:47 p.m.