Triple
T12472408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio-class SSBN |
E298091
|
entity |
| Predicate | conversionProgram |
P105178
|
FINISHED |
| Object | four units converted to SSGN |
—
|
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: four units converted to SSGN | Statement: [Ohio-class SSBN, conversionProgram, four units converted to SSGN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conversionProgram Context triple: [Ohio-class SSBN, conversionProgram, four units converted to SSGN]
-
A.
conversionProcess
Indicates a process in which something is transformed or changed from one state, form, or representation into another.
-
B.
conversionTarget
Indicates that one entity serves as the intended outcome, goal, or result that another entity is meant to be converted or transformed into.
-
C.
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.
-
D.
conversionName
Indicates that one entity is the name or label assigned to a specific conversion event or conversion process associated with another entity.
-
E.
conversionWave
Indicates a process in which changes or transformations spread through entities or states in a sequential, wave-like manner.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e5f8d04819086d1ad4d62364005 |
completed | April 10, 2026, 7:24 p.m. |
Created at: April 8, 2026, 9:56 p.m.