Triple
T14770699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steven Conrad |
E347123
|
entity |
| Predicate | wroteScreenplayFor |
P15305
|
FINISHED |
| Object | Wonder |
E554427
|
NE FINISHED |
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: [Steven Conrad, wroteScreenplayFor, Wonder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wonder Context triple: [Steven Conrad, wroteScreenplayFor, 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.
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.
-
D.
The Wonders
The Wonders are the fictional 1960s pop band from the film "That Thing You Do!", known for their catchy one-hit-wonder title track and Beatles-inspired image.
-
E.
Wish
Wish is an e-commerce platform and mobile shopping app known for offering a wide variety of low-priced goods shipped directly from merchants, primarily in China, to consumers worldwide.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec81334e08190a77d760e507d00ed |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24b41df881908119e183b8299c48 |
completed | May 8, 2026, 6 p.m. |
Created at: April 10, 2026, 1:31 a.m.