Triple
T9569195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columna Centenaria Divi Marci Aurelii |
E230870
|
entity |
| Predicate | topStatueReplacedIn |
P64961
|
FINISHED |
| Object | 1589 |
—
|
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: 1589 | Statement: [Columna Centenaria Divi Marci Aurelii, topStatueReplacedIn, 1589]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topStatueReplacedIn Context triple: [Columna Centenaria Divi Marci Aurelii, topStatueReplacedIn, 1589]
-
A.
statueRemovedBy
Indicates that a statue was taken down, dismantled, or otherwise removed by a specified agent or authority.
-
B.
previousRoofStatue
chosen
Indicates that one entity served as the earlier or former roof statue relative to another entity.
-
C.
statueName
Indicates that a statue has a specific name or title associated with it.
-
D.
hasStatue
Indicates that one entity possesses, contains, or is associated with a statue representing or located within it.
-
E.
replacedTrophy
Indicates that one entity has taken the place of another entity in serving as a trophy or awarded symbol of achievement.
- 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_69ca847f22188190a56e4a97625bef22 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd998940c881909f9025512cf72fe9 |
completed | April 1, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:04 p.m.