Triple
T3368280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Majorian |
E70888
|
entity |
| Predicate | legalReformsConcerned |
P39456
|
FINISHED |
| Object | treatment of senators |
—
|
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: treatment of senators | Statement: [Majorian, legalReformsConcerned, treatment of senators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalReformsConcerned Context triple: [Majorian, legalReformsConcerned, treatment of senators]
-
A.
relatedLegislation
Indicates that there exists a legislative document that is connected to, affects, or is otherwise relevant to the subject entity.
-
B.
legalDoctrineChallenged
Indicates that a particular legal doctrine is being disputed, questioned, or contested, typically through litigation or formal legal argument.
-
C.
legalAmendment
Indicates a formal change or modification made to an existing law, regulation, or legal document.
-
D.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
-
E.
goalOfReforms
chosen
Indicates that a reform or set of reforms is undertaken with the aim or intended objective of achieving a particular outcome.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28a813c81909d1c71fe577e6681 |
completed | March 8, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69ada4317e288190ab7d0f66e9dba65f |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.