Triple
T471767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frisch–Peierls memorandum |
E8572
|
entity |
| Predicate | typeOfAnalysis |
P11082
|
FINISHED |
| Object | theoretical calculation of critical mass |
—
|
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: theoretical calculation of critical mass | Statement: [Frisch–Peierls memorandum, typeOfAnalysis, theoretical calculation of critical mass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAnalysis Context triple: [Frisch–Peierls memorandum, typeOfAnalysis, theoretical calculation of critical mass]
-
A.
analyzes
Indicates that one entity systematically examines or evaluates another entity to understand its nature, structure, or components.
-
B.
typeOfInvestigation
chosen
Indicates the specific kind or category of investigation being conducted or referred to in the relationship.
-
C.
typeOfAudit
Indicates the specific category or kind of audit being performed or referenced in relation to an entity.
-
D.
hasRegressionAnalysis
Indicates that a regression analysis has been performed on, or is associated with, a given dataset, model, or relationship between variables.
-
E.
derivationType
Indicates the specific manner or process by which one entity is derived or obtained from 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eff0ca408190958405aec2ec6f53 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edecefb081908331ef8b9edf6636 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.