Triple
T29410984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia the Elder |
E745892
|
entity |
| Predicate | marriageOrderOfSpouseTiberius |
P4764
|
FINISHED |
| Object | third husband |
—
|
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: third husband | Statement: [Julia the Elder, marriageOrderOfSpouseTiberius, third husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageOrderOfSpouseTiberius Context triple: [Julia the Elder, marriageOrderOfSpouseTiberius, third husband]
-
A.
marriedToEmperor
Indicates that one entity is the spouse of an emperor, signifying a marital relationship to a reigning or titled emperor.
-
B.
marriageOrderWithJuliaTheElder
Indicates the sequence or arrangement of marriages involving Julia the Elder in relation to other spouses or partners.
-
C.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
D.
startTime (marriage to Nero)
Indicates the point in time when the marriage to Nero began.
-
E.
motherSpouseOrder
Indicates that the subject is the spouse of the object’s mother, with an ordering or ranking among multiple such spouses.
- 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_69f0a79eb7d081908c67197a5f347e68 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 28, 2026, 2:57 p.m.