Triple
T8885335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logainne Schwartzandgrubenierre |
E211514
|
entity |
| Predicate | politicalAwareness |
P85533
|
FINISHED |
| Object | strong |
—
|
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: strong | Statement: [Logainne Schwartzandgrubenierre, politicalAwareness, strong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalAwareness Context triple: [Logainne Schwartzandgrubenierre, politicalAwareness, strong]
-
A.
politicalIssueFor
Indicates a relationship where a particular topic, problem, or policy area is considered a matter of political concern or debate for a given entity.
-
B.
politicalIssueIn
Indicates that a political issue is relevant to, occurs within, or is associated with a particular geographic or political region.
-
C.
politicalCurrent
Indicates that an entity is presently holding or engaged in a specific political role, status, or activity at the current time.
-
D.
currentPoliticalTrend
Indicates the prevailing direction or pattern of political attitudes, behaviors, or power dynamics at a given time.
-
E.
politicalTheme
Indicates that something is related to, characterized by, or primarily concerned with politics, governance, or political issues.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc618bd30881909e54d0708f144786 |
completed | April 1, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5d6e54808190af4156edd4c8ffbc |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 6:53 p.m.