Triple
T16189050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senafe |
E392885
|
entity |
| Predicate | hasNearbyArchaeologicalSite |
P14422
|
FINISHED |
| Object | Metera |
E392887
|
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: Metera | Statement: [Senafe, hasNearbyArchaeologicalSite, Metera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metera Context triple: [Senafe, hasNearbyArchaeologicalSite, Metera]
-
A.
Metera
chosen
Metera is an important archaeological site in Eritrea known for its ancient ruins and inscriptions reflecting the region’s early civilizations.
-
B.
Meter Kubileya
Meter Kubileya is an ancient Anatolian mother goddess, later worshipped in the Greco-Roman world as Cybele, associated with fertility, mountains, and wild nature.
-
C.
Mechta
Mechta is the alternative name for Luna 1, the Soviet spacecraft that became the first human-made object to reach the vicinity of the Moon and enter a heliocentric orbit.
-
D.
Matareya
Matareya is a district in northeastern Cairo, Egypt, known for its ancient Heliopolis archaeological remains and historic religious sites.
-
E.
Mera
Mera is a powerful Atlantean warrior and sorceress from DC Comics, best known as Aquaman’s ally and queen of Atlantis.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d3a8e48190bdf29a633f4b0490 |
completed | April 17, 2026, 12:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff0750f08190a2fce65124d8dcc0 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.