Triple
T14526932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eric Larson |
E340802
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Cinderella |
E208251
|
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: Cinderella | Statement: [Eric Larson, notableWork, Cinderella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cinderella Context triple: [Eric Larson, notableWork, Cinderella]
-
A.
Cinderella
"Cinderella" is a popular studio album by Tanzanian singer Ali Kiba that helped solidify his status in the East African music scene.
-
B.
Cinderella
Cinderella is a musical by Andrew Lloyd Webber that reimagines the classic fairy tale with a modern twist in story, character, and score.
-
C.
Cendrillon
Cendrillon is a French opera by Jules Massenet that offers a lyrical, romantic adaptation of the Cinderella fairy tale.
-
D.
Cinderella (fairy tale)
chosen
Cinderella (fairy tale) is a classic European folk story about a mistreated young woman whose life is transformed through magical intervention and a royal romance, popularized by countless literary and film adaptations.
-
E.
La Cenerentola
La Cenerentola is an opera buffa by Gioachino Rossini that offers a comic, bel canto reimagining of the Cinderella fairy tale.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea050781881909ed685d94479bf99 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a52260881909a0d85603666107d |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.