Triple
T34290972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicola Murray |
E879886
|
entity |
| Predicate | politicalExperienceLevel |
P197032
|
FINISHED |
| Object | inexperienced |
—
|
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: inexperienced | Statement: [Nicola Murray, politicalExperienceLevel, inexperienced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalExperienceLevel Context triple: [Nicola Murray, politicalExperienceLevel, inexperienced]
-
A.
governingExperience
Indicates that an entity has experience in governing or exercising authority over others or over an organization, territory, or system.
-
B.
stateLegislativeExperience
Indicates that an entity has previously served in, or held a position within, a state-level legislative body.
-
C.
hasLeadershipExperienceIn
Indicates that an entity possesses prior leadership experience specifically within a given domain, context, or organization.
-
D.
localGovernmentExperience
Indicates that an entity has held a role or performed duties within a local or municipal government context.
-
E.
yearsActiveInPolitics
Indicates the span of time during which an entity has been actively involved in political roles, activities, or office.
- 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_69f349b6df1c81908e5e5b6c2ab6409b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe744faca881908e11e90e0a35653f |
completed | May 8, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69fe734cbf7081909a552c5cf3b5ea59 |
completed | May 8, 2026, 11:35 p.m. |
| PDg | Predicate description generation | batch_69fe744e9ee081909b362fc8609bc744 |
completed | May 8, 2026, 11:39 p.m. |
Created at: May 1, 2026, 1:57 a.m.