Triple
T11562911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vima Kadphises |
E274186
|
entity |
| Predicate | usedTitle |
P3254
|
FINISHED |
| Object | Soter Megas |
E30031
|
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: Soter Megas | Statement: [Vima Kadphises, usedTitle, Soter Megas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soter Megas Context triple: [Vima Kadphises, usedTitle, Soter Megas]
-
A.
Soter
chosen
Soter is a Greek term meaning "savior" or "deliverer," often used as a title for deities or revered figures who provide salvation or protection.
-
B.
Cleon
Cleon was an influential Athenian statesman and general during the Peloponnesian War, known for his aggressive policies and prominent role in Athenian politics.
-
C.
Megaris
Megaris was an ancient Greek region in central Greece, situated between Attica and Corinthia and centered around the city-state of Megara.
-
D.
Azarethes
Azarethes was a prominent Sasanian Persian general noted for his role in the Iberian War against the Eastern Roman (Byzantine) Empire.
-
E.
Dilios
Dilios is the Spartan soldier and narrator in the film "300," known for recounting King Leonidas's stand at Thermopylae.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd2016481909b33848af3d1d6c1 |
completed | April 10, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e89e73b481908175576f4ec8d39a |
completed | April 21, 2026, 3:01 a.m. |
Created at: April 8, 2026, 9:37 p.m.