Triple
T8393853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia Antonia |
E198005
|
entity |
| Predicate | firstHusbandInstanceOf |
P81982
|
FINISHED |
| Object | Roman politician |
—
|
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: Roman politician | Statement: [Julia Antonia, firstHusbandInstanceOf, Roman politician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstHusbandInstanceOf Context triple: [Julia Antonia, firstHusbandInstanceOf, Roman politician]
-
A.
firstWifeOf
Indicates that one person is the first woman to have been married to another person.
-
B.
firstHolderSpouseOf
Indicates that the first holder in the relation is the spouse (married partner) of the other holder.
-
C.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
D.
firstHusbandDeath
Indicates that the woman's first husband has died, marking the end of that marital relationship by his death.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8185ef60819085cfa7491d35834a |
completed | March 31, 2026, 8:10 a.m. |
| PD | Predicate disambiguation | batch_69cb70d24b248190a326aa6804f942b5 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb77690720819099de1e22b84a9563 |
completed | March 31, 2026, 7:27 a.m. |
Created at: March 30, 2026, 6:03 p.m.