Triple
T37591598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fausta Cornelia |
E935272
|
entity |
| Predicate | marriageHasPoliticalSignificance |
P50599
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Fausta Cornelia, marriageHasPoliticalSignificance, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageHasPoliticalSignificance Context triple: [Fausta Cornelia, marriageHasPoliticalSignificance, true]
-
A.
marriageSignificance
Indicates the importance, impact, or meaningfulness that a marriage holds within a given context or for the entities involved.
-
B.
marriageControversyInvolved
Indicates that an entity is involved in a dispute, scandal, or public controversy related to a marriage.
-
C.
politicalPurposeOfMarriage
chosen
Indicates that a marriage is entered into or used primarily for political objectives, such as gaining power, forming alliances, or influencing governance.
-
D.
marriedToPolitician
Indicates that a person is married to someone who holds or has held a political office or role.
-
E.
regardsMarriageAs
Indicates that one entity holds a particular view, attitude, or evaluative stance toward the institution or concept of marriage.
- 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_69f76ecf39c081909baffe597bb55273 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe00dad1708190b6522476bebb43af |
completed | May 8, 2026, 3:27 p.m. |
| PD | Predicate disambiguation | batch_69fdfc3717f48190bb50ac2919c8ef95 |
completed | May 8, 2026, 3:07 p.m. |
Created at: May 3, 2026, 4:18 p.m.