Triple
T25371890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NFA |
E632951
|
entity |
| Predicate | conversionMethod |
P48524
|
FINISHED |
| Object | subset construction |
—
|
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: subset construction | Statement: [NFA, conversionMethod, subset construction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conversionMethod Context triple: [NFA, conversionMethod, subset construction]
-
A.
methodOfConversion
chosen
Indicates the specific process or technique used to transform one form, state, or representation into another.
-
B.
conversionProcess
Indicates a process in which something is transformed or changed from one state, form, or representation into another.
-
C.
conversionTarget
Indicates that one entity serves as the intended outcome, goal, or result that another entity is meant to be converted or transformed into.
-
D.
conversionOperator
Indicates that one entity defines or provides a way to be automatically or explicitly converted into another entity or type.
-
E.
conversionUse
Indicates that one entity is used as a means, method, or context for converting another entity from one form, state, or representation to another.
- 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_69e75a90c0dc819092f928b6ea0ecc72 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 1:38 p.m.