Triple
T16407261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramesses IV |
E398466
|
entity |
| Predicate | nomen |
P744
|
FINISHED |
| Object | Ramesses |
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: Ramesses | Statement: [Ramesses IV, nomen, Ramesses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramesses Context triple: [Ramesses IV, nomen, Ramesses]
-
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 Amunherkhepeshef
Ramesses Amunherkhepeshef was the birth name of the ancient Egyptian pharaoh Ramesses VI of the Twentieth Dynasty.
-
D.
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.
-
E.
Kahmunrah
Kahmunrah is the power-hungry ancient Egyptian pharaoh and main antagonist in the film "Night at the Museum: Battle of the Smithsonian."
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d36b808190b6b8c412ae0d2faa |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b276be5c8190a42ce541168ab7d0 |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:09 a.m.