Triple
T12776961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radjedef |
E305401
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Setka |
E255750
|
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: Setka | Statement: [Radjedef, child, Setka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Setka Context triple: [Radjedef, child, Setka]
-
A.
Setka
chosen
Setka was an ancient Egyptian prince of the 4th Dynasty, likely a son of Pharaoh Djedefre, known from statues and inscriptions found at Abu Rawash.
-
B.
Alexeyevsk
Alexeyevsk is the former name of the Russian town now known as Belogorsk, located in Amur Oblast in the Russian Far East.
-
C.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
-
D.
Sestroretsk
Sestroretsk is a town in northwestern Russia, now part of Saint Petersburg, historically known for its arms factory and seaside resort area on the Gulf of Finland.
-
E.
Sovetskaya Gavan
Sovetskaya Gavan is a port town on the Strait of Tartary in Russia’s Far East, serving as an important maritime and transport hub in Khabarovsk Krai.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e595e008190b42dff3012d17d66 |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8c75a048190aee92e50017c214e |
completed | May 3, 2026, 2:53 a.m. |
Created at: April 9, 2026, 5:29 p.m.