Triple
T22237835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anqet |
E549637
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Satet |
—
|
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: Satet | Statement: [Anqet, relatedTo, Satet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satet Context triple: [Anqet, relatedTo, Satet]
-
A.
Satet
chosen
Satet is an ancient Egyptian goddess associated with the Nile’s annual inundation, fertility, and protection, particularly venerated at Elephantine near Egypt’s southern border.
-
B.
Matrah
Matrah is a historic coastal town in Oman that served as a key trading port and commercial hub during the height of Omani maritime power.
-
C.
Saqar
Saqar is a term in the Qur'an referring to a severe level of Hell associated with intense punishment for disbelievers.
-
D.
Merowe
Merowe is a town in northern Sudan situated along the Nile River, known for its proximity to the Fourth Cataract and nearby archaeological and dam sites.
-
E.
Shetebo
Shetebo are an indigenous people of the Peruvian Amazon closely related culturally and linguistically to the Shipibo-Conibo.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f13210eb9c8190bc40d06c393e0d9a |
completed | April 28, 2026, 10:17 p.m. |
Created at: April 16, 2026, 8:38 p.m.