Triple
T11328869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Prince of Egypt |
E268292
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Rameses |
E72895
|
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: Rameses | Statement: [The Prince of Egypt, mainCharacter, Rameses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rameses Context triple: [The Prince of Egypt, mainCharacter, Rameses]
-
A.
Rameses
Rameses is the ram mascot of the University of North Carolina at Chapel Hill, symbolizing the school's athletic teams and spirit.
-
B.
Pi-Ramesses
Pi-Ramesses was a major royal city in the Nile Delta that served as the principal residence and power center of Ramesses II during Egypt’s New Kingdom.
-
C.
Ramesses II
chosen
Ramesses II was a powerful 19th Dynasty pharaoh of ancient Egypt, renowned for his extensive building projects, military campaigns, and exceptionally long reign.
-
D.
Kahmunrah
Kahmunrah is the power-hungry ancient Egyptian pharaoh and main antagonist in the film "Night at the Museum: Battle of the Smithsonian."
-
E.
Ramses, King of the Nile
"Ramses, King of the Nile" is a film featuring actor Don DeFore in a story centered on ancient Egypt and its legendary pharaoh.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e330008190b75490efde01dc59 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e54318be088190b57de40a2091447d |
completed | April 19, 2026, 9:03 p.m. |
Created at: April 8, 2026, 9:32 p.m.