Triple
T19489258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bakenranef |
E487603
|
entity |
| Predicate | reignedFrom |
P87123
|
FINISHED |
| Object | Sais |
—
|
NE NERFINISHED |
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: Sais | Statement: [Bakenranef, reignedFrom, Sais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sais Context triple: [Bakenranef, reignedFrom, Sais]
-
A.
Sais
chosen
Sais was an ancient Egyptian city in the western Nile Delta that served as a significant religious and political center, especially prominent during the 26th (Saite) Dynasty.
-
B.
Saisiyat
The Saisiyat are one of Taiwan’s indigenous Austronesian-speaking peoples, known for their distinctive culture and the legendary Pasta’ay (Dwarf) ritual.
-
C.
Saffais
Saffais is a small commune in the Meurthe-et-Moselle department of northeastern France.
-
D.
Sahurs
Sahurs is a small commune in northern France, situated along the Seine River in the Normandy region.
-
E.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6348ad4088190b530f47efca90165 |
completed | April 20, 2026, 2:13 p.m. |
Created at: April 10, 2026, 1:39 p.m.