Triple
T24488253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Pitcairn |
E617572
|
entity |
| Predicate | notableUserPoliticalAlignment |
P78376
|
FINISHED |
| Object | communist |
—
|
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: communist | Statement: [Frank Pitcairn, notableUserPoliticalAlignment, communist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableUserPoliticalAlignment Context triple: [Frank Pitcairn, notableUserPoliticalAlignment, communist]
-
A.
associatedWithPoliticalAlignment
Indicates a relationship where an entity is connected to, supports, or is characterized by a particular political ideology, party, or alignment.
-
B.
hasAuthorPoliticalAlignment
chosen
Indicates that an author is associated with or identified as having a particular political alignment or ideology.
-
C.
designerPoliticalAffiliation
Indicates the political party, ideology, or affiliation associated with a designer.
-
D.
holderPoliticalAffiliation
Indicates that a person or officeholder is associated with or belongs to a particular political party or ideology.
-
E.
politicalAlignmentOfNotableMembers
Indicates the political ideologies or affiliations associated with notable members of a group, organization, or 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_69e2d7f4e6bc8190aec540ae3b9ed7f2 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:22 a.m.