Triple
T532633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montford Reforms |
E12255
|
entity |
| Predicate | reservedSubjectsIncluded |
P1393
|
FINISHED |
| Object | law and order |
—
|
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: law and order | Statement: [Montford Reforms, reservedSubjectsIncluded, law and order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reservedSubjectsIncluded Context triple: [Montford Reforms, reservedSubjectsIncluded, law and order]
-
A.
isSubjectTo
Indicates that one entity is governed, affected, or constrained by the authority, rules, conditions, or influence of another entity.
-
B.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
C.
reservedFor
Indicates that something is set aside or allocated specifically for the use, benefit, or purpose of a particular entity or group.
-
D.
decisionsSubjectTo
Indicates that certain decisions are constrained by, dependent on, or must comply with specified conditions, approvals, or oversight.
-
E.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b3e49081909810fa417b31306f |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.