Triple
T3567167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logan Killicks |
E75476
|
entity |
| Predicate | viewOfMarriage |
P1107
|
FINISHED |
| Object | marriage as work and security |
—
|
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: marriage as work and security | Statement: [Logan Killicks, viewOfMarriage, marriage as work and security]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewOfMarriage Context triple: [Logan Killicks, viewOfMarriage, marriage as work and security]
-
A.
marriageContext
Indicates the situational or cultural circumstances under which a marriage occurs or exists, such as legal, social, or religious conditions surrounding the marital relationship.
-
B.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
C.
positionOnMarriage
chosen
Indicates a person's stance, opinion, or policy regarding the institution or practice of marriage.
-
D.
marriagePattern
Indicates the typical form or structure of a marriage relationship, such as how partners are selected, organized, or related within a social or cultural system.
-
E.
marries
Indicates that one entity enters into a legally or socially recognized marital union with another entity.
- 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_69ad85d512708190829c8b2d3a2ccfb8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0ab51d881908f004fae47ab09d9 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb834779081908468e182d5f6cf02 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.