Triple
T18037702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pauline Bonaparte, Princess Borghese (sculpture) |
E431553
|
entity |
| Predicate | depictsAs |
P53700
|
FINISHED |
| Object | Venus |
—
|
NE NERFINISHED |
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 | Statement: [Pauline Bonaparte, Princess Borghese (sculpture), depictsAs, Venus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Venus Context triple: [Pauline Bonaparte, Princess Borghese (sculpture), depictsAs, Venus]
-
A.
Venus
Venus is a character in the action film "Crank: High Voltage," known for her involvement in the movie’s chaotic, high-energy storyline.
-
B.
Venus
Venus is the second planet from the Sun, known for its dense, toxic atmosphere, extreme surface temperatures, and bright visibility in Earth's sky.
-
C.
Venus
chosen
Venus is the Roman goddess of love, beauty, and fertility, often depicted as the divine ancestor and protector of Aeneas and the Roman people.
-
D.
Venus
Venus is a small suburban town within the greater Dallas–Fort Worth metropolitan area in Texas.
-
E.
Venus
Venus is a Romanian Black Sea seaside resort town in Constanța County, known for its beaches and tourism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be3bc3208190a6db569e79f06232 |
completed | April 19, 2026, 11:36 a.m. |
Created at: April 10, 2026, 10:25 a.m.