Triple
T669669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apollo |
E12942
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Asclepius |
E28749
|
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: Asclepius | Statement: [Apollo, child, Asclepius]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asclepius Context triple: [Apollo, child, Asclepius]
-
A.
Asclepius
chosen
Asclepius is the ancient Greek god of medicine and healing, revered for his ability to cure illness and restore health.
-
B.
Dorotheus
Dorotheus was a 6th-century Byzantine jurist who helped systematize and codify Roman law under Emperor Justinian I.
-
C.
Dioscorus
Dioscorus is traditionally depicted in Christian hagiography as the pagan father of Saint Barbara who opposed her conversion and ultimately martyred her.
-
D.
Menoetius
Menoetius is a Titan in Greek mythology, known as a son of Iapetus and Clymene and the father of the hero Patroclus.
-
E.
Cirón
Cirón is a river in southwestern France known for flowing through the Sauternes wine region, where its cool misty microclimate helps produce the area’s famous sweet wines.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49ffbe09881909b547a52a6b34c7f |
completed | March 1, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5c39d11508190a3bd0f118d122e1a |
completed | March 2, 2026, 5:06 p.m. |
Created at: March 1, 2026, 7:36 p.m.