Triple
T30215000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clodia Metelli |
E768178
|
entity |
| Predicate | husbandHeldOffice |
P56754
|
FINISHED |
| Object | consul of the Roman Republic |
—
|
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: consul of the Roman Republic | Statement: [Clodia Metelli, husbandHeldOffice, consul of the Roman Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: husbandHeldOffice Context triple: [Clodia Metelli, husbandHeldOffice, consul of the Roman Republic]
-
A.
spouseLaterOffice
chosen
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
-
B.
spouseOffice
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
C.
roleDuringHusbandPresidency
Indicates the role or position a person held specifically during her husband's term as president.
-
D.
heldPoliticalOfficeIn
Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
-
E.
spouseNumberOfTermsInOffice
Indicates the number of distinct terms in office that the spouse of the referenced entity has served.
- 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_69f2247fd8b8819087fcf83cb7a05eb8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67ff517908190ad290edafd6c6f5f |
completed | May 2, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:33 p.m.