Triple
T4330512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aladdin (2019 film) |
E96736
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Rideback |
E409657
|
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: Rideback | Statement: [Aladdin (2019 film), productionCompany, Rideback]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rideback Context triple: [Aladdin (2019 film), productionCompany, Rideback]
-
A.
Rideback
chosen
Rideback is a film and television production company founded by producer Dan Lin, known for backing major Hollywood franchises and high-profile studio projects.
-
B.
Vacallo
Vacallo is a small municipality in the canton of Ticino in southern Switzerland, located near the Italian border.
-
C.
Rider
Rider is a cross-platform integrated development environment by JetBrains, widely used for .NET and C# development.
-
D.
Darkhorse
Darkhorse is the storied nickname of the U.S. Marine Corps’ 3rd Battalion, 5th Marines, renowned for its combat service and battlefield sacrifices.
-
E.
Ramolino
Ramolino is an Italian surname historically associated with Corsican nobility and notably borne by Letizia Ramolino, the mother of Napoleon Bonaparte.
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3514c39748190900e13e70ed8848c |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d09fad588190b488012b4fc6cb8c |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:13 p.m.