Triple
T33096505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cut-elimination theorem |
E846922
|
entity |
| Predicate | concernsRule |
P181365
|
FINISHED |
| Object | cut rule |
—
|
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: cut rule | Statement: [cut-elimination theorem, concernsRule, cut rule]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concernsRule Context triple: [cut-elimination theorem, concernsRule, cut rule]
-
A.
concernsClause
Indicates that one entity (such as a document, statement, or discussion) is about, relates to, or addresses a particular clause.
-
B.
concernsProvision
Indicates a relationship where something is about, deals with, or relates to the supplying or making available of resources, services, or necessities.
-
C.
concernsSet
Indicates that something is about, relates to, or involves a particular set as its primary subject or focus.
-
D.
concernsFeature
Indicates that something is about, relates to, or involves a particular feature.
-
E.
subjectOfConcernFor
Indicates that one entity is regarded as a matter of worry, interest, or attention for another entity.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
| PDg | Predicate description generation | batch_69f7688cea58819098bdfd7c80df7634 |
completed | May 3, 2026, 3:23 p.m. |
Created at: May 1, 2026, 1:26 a.m.