Triple
T2814626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arethusa |
E54251
|
entity |
| Predicate | hasMythCycle |
P9998
|
FINISHED |
| Object | myths of Sicily and Syracuse |
—
|
LITERAL 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: myths of Sicily and Syracuse | Statement: [Arethusa, hasMythCycle, myths of Sicily and Syracuse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMythCycle Context triple: [Arethusa, hasMythCycle, myths of Sicily and Syracuse]
-
A.
hasMythType
chosen
Indicates that an entity is associated with or classified under a particular type or category of myth.
-
B.
hasMythSource
Indicates that something derives from, is based on, or is supported by a particular myth or mythological source.
-
C.
hasMythicMotif
Indicates that one entity features, embodies, or is associated with a particular mythic motif found in the other entity.
-
D.
hasMythicTheme
Indicates that something embodies, references, or is characterized by a mythic or mythological theme.
-
E.
hasMystery
Indicates that one entity possesses, contains, or is associated with something unknown, secret, or unexplained in relation to another entity.
- F. None of above.
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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4d29488190a32461906dd9ea7e |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.