Triple
T16169121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temples of Venus |
E392386
|
entity |
| Predicate | hasDeityAspect |
P73550
|
FINISHED |
| Object | Venus Cloacina |
E500453
|
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: Venus Cloacina | Statement: [Temples of Venus, hasDeityAspect, Venus Cloacina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Venus Cloacina Context triple: [Temples of Venus, hasDeityAspect, Venus Cloacina]
-
A.
Venus Cloacina
chosen
Venus Cloacina is an aspect of the Roman goddess Venus associated with purification and the Cloaca Maxima, the great sewer of ancient Rome.
-
B.
Venusia
Venusia was an important ancient city of Lucania in southern Italy, known for its strategic location and Roman colonial history.
-
C.
Vulcanal
Vulcanal is an ancient open-air shrine in the Roman Forum dedicated to Vulcan, the Roman god of fire and metalworking.
-
D.
VenusFort
VenusFort was a Venice-themed shopping and entertainment mall in Tokyo’s Odaiba district, known for its faux European streetscape and outlet stores.
-
E.
Venus Anadyomene
Venus Anadyomene is a classical artistic motif depicting the goddess Venus (Aphrodite) rising from the sea, often shown wringing water from her hair.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb5e6d881908749683091afa90c |
completed | April 17, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fffefc3e088190975ecbdaeba7ee84 |
completed | May 10, 2026, 3:43 a.m. |
Created at: April 10, 2026, 5:02 a.m.