Triple
T18286271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Half-Breed faction of the Republican Party |
E437991
|
entity |
| Predicate | hasPejorativeName |
P131184
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Half-Breed faction of the Republican Party, hasPejorativeName, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPejorativeName Context triple: [Half-Breed faction of the Republican Party, hasPejorativeName, true]
-
A.
hasPejorativeOrigin
Indicates that the referenced term, label, or expression originates from a disparaging, derogatory, or contemptuous usage or context.
-
B.
languageOfEpithet
Indicates the language in which an epithet (such as a descriptive or honorary title) is expressed.
-
C.
hasMeaningOfEpithet
Indicates that one entity expresses or conveys the meaning or sense of another entity’s epithet.
-
D.
containsProfanity
Indicates that the referenced content includes one or more profane, vulgar, or offensive expressions.
-
E.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500fa2f308190a4744a4ed630b8d9 |
completed | April 19, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:35 a.m.