Triple
T30199009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Morrow (politician) |
E767718
|
entity |
| Predicate | hasParticularOpinion |
P32222
|
FINISHED |
| Object | strongly critical of establishment Republicans |
—
|
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: strongly critical of establishment Republicans | Statement: [Robert Morrow (politician), hasParticularOpinion, strongly critical of establishment Republicans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticularOpinion Context triple: [Robert Morrow (politician), hasParticularOpinion, strongly critical of establishment Republicans]
-
A.
hasDifferentOpinionsOn
Indicates that two or more entities hold differing views or judgments regarding a particular topic, issue, or subject.
-
B.
givesOpinionOn
chosen
Indicates that one entity expresses a view, judgment, or evaluation about another entity or subject.
-
C.
opinionBy
Indicates that a particular opinion, viewpoint, or judgment is expressed or held by a specific entity.
-
D.
hasOpinionSection
Indicates that something includes or is associated with a dedicated opinion section.
-
E.
hasSeparateOpinions
Indicates that the related entities hold distinct or differing views, judgments, or beliefs about a subject.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdf5d05cc481909ec9e1b1f0784279 |
completed | May 8, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69fdf0cdd6948190838864ab3120dfa6 |
completed | May 8, 2026, 2:18 p.m. |
Created at: April 29, 2026, 7:30 p.m.