Triple
T204596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCulloch v. Maryland |
E4582
|
entity |
| Predicate | decision |
P5063
|
FINISHED |
| Object | in favor of McCulloch and the federal government |
—
|
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: in favor of McCulloch and the federal government | Statement: [McCulloch v. Maryland, decision, in favor of McCulloch and the federal government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decision Context triple: [McCulloch v. Maryland, decision, in favor of McCulloch and the federal government]
-
A.
decisionType
Indicates the specific category or nature of a decision associated with an entity or event.
-
B.
decides
Indicates that an entity makes a choice or determination between options, often resolving uncertainty or selecting a course of action.
-
C.
decisionLanguage
Indicates that a decision, statement, or choice is expressed or recorded in a particular natural language.
-
D.
decidesOn
Indicates that an agent makes a choice or determination regarding a particular option, issue, or course of action.
-
E.
resolution
chosen
Indicates the act of formally deciding, settling, or expressing a determined stance on an issue, often through an official decision or statement.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25f46b4f081909e5ee3718109a71f |
completed | Feb. 28, 2026, 3:21 a.m. |
| PD | Predicate disambiguation | batch_69a25b4b42ec8190bef16bbbdd30a742 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.