Triple
T1772029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin F. Butler |
E38895
|
entity |
| Predicate | legalConceptCoined |
P118
|
FINISHED |
| Object | contraband of war (applied to escaped slaves) |
—
|
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: contraband of war (applied to escaped slaves) | Statement: [Benjamin F. Butler, legalConceptCoined, contraband of war (applied to escaped slaves)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalConceptCoined Context triple: [Benjamin F. Butler, legalConceptCoined, contraband of war (applied to escaped slaves)]
-
A.
legalConcept
Indicates a relationship where something is classified or treated as a concept defined and governed by law or legal theory.
-
B.
coinedTerm
chosen
Indicates that an entity originated and introduced a particular term or expression into use.
-
C.
legalTermUsedFrom
Indicates that a particular legal term has been in official or recognized use starting from a specified point in time.
-
D.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
E.
legalDefinitionCameIntoForce
Indicates that a particular legal definition officially became valid and enforceable from a specified point in time.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab39fc2c448190bfaf1ee8d474632a |
completed | March 6, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69aa61cbb1288190a7ba38b61905f578 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.