Triple
T58980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon entropy |
E1168
|
entity |
| Predicate | quantifies |
P4227
|
FINISHED |
| Object | average uncertainty of a random variable |
—
|
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: average uncertainty of a random variable | Statement: [Shannon entropy, quantifies, average uncertainty of a random variable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quantifies Context triple: [Shannon entropy, quantifies, average uncertainty of a random variable]
-
A.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
-
B.
analyzes
Indicates that one entity systematically examines or evaluates another entity to understand its nature, structure, or components.
-
C.
volume
Indicates the amount of three-dimensional space an entity occupies or contains.
-
D.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
E.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
- 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_69a24a552ef88190a0df287d68c65cba |
completed | Feb. 28, 2026, 1:52 a.m. |
| NER | Named-entity recognition | batch_69a250e401288190ba12322c9c5f07c9 |
completed | Feb. 28, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69a24e9f40908190a2f4a2111469b733 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a250e2a80881909e5a653260e6f8e0 |
completed | Feb. 28, 2026, 2:20 a.m. |
Created at: Feb. 28, 2026, 1:55 a.m.