Triple
T30331884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aulus Hirtius |
E771502
|
entity |
| Predicate | consulshipWith |
P169730
|
FINISHED |
| Object | Gaius Vibius Pansa Caetronianus |
—
|
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: Gaius Vibius Pansa Caetronianus | Statement: [Aulus Hirtius, consulshipWith, Gaius Vibius Pansa Caetronianus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consulshipWith Context triple: [Aulus Hirtius, consulshipWith, Gaius Vibius Pansa Caetronianus]
-
A.
consulship
Indicates the relationship in which an individual holds or exercises the office and powers of a consul.
-
B.
consulshipYear
Indicates the specific year during which an entity held or is associated with a consulship office or term.
-
C.
precededInConsulshipBy
Indicates that one consul’s term of office occurred immediately before another consul’s term.
-
D.
numberOfConsulships
Indicates the total count of times an entity has held the office or role of consul.
-
E.
succeededInConsulshipBy
Indicates that one individual’s term in the consulship was immediately followed by another individual’s term in the same office.
- F. None of above. chosen
Provenance (4 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f681c86c648190896da5ce6be325ae |
completed | May 2, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f7e116c819099aec724e9ef3763 |
completed | May 2, 2026, 10:49 p.m. |
Created at: April 29, 2026, 7:53 p.m.