Triple
T5049997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joshua R. Giddings |
E113760
|
entity |
| Predicate | reason for censure |
P60877
|
FINISHED |
| Object | introducing antislavery resolutions related to the Creole case |
—
|
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: introducing antislavery resolutions related to the Creole case | Statement: [Joshua R. Giddings, reason for censure, introducing antislavery resolutions related to the Creole case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reason for censure Context triple: [Joshua R. Giddings, reason for censure, introducing antislavery resolutions related to the Creole case]
-
A.
censorshipReason
Indicates the justification or cause given for why certain content is suppressed, restricted, or removed.
-
B.
canCensure
Indicates that one entity has the authority or power to formally reprimand, criticize, or express disapproval of another entity’s actions or behavior.
-
C.
reasonForExcommunication
Indicates the specific cause or grounds that led to an entity’s excommunication.
-
D.
reasonForPunishment
Indicates that one entity is the cause, justification, or grounds for another entity receiving a punishment.
-
E.
reasonForBan
Indicates the justification or cause that led to an entity being banned.
- 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_69bd44391fc48190a311ce9c826c209b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7425df74819091cfde348dd16a68 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd715479f08190933604aebd34414f |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:37 p.m.