Triple
T244384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avogadro constant |
E5003
|
entity |
| Predicate | isCategory |
P87
|
FINISHED |
| Object | microscopic to macroscopic conversion factor |
—
|
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: microscopic to macroscopic conversion factor | Statement: [Avogadro constant, isCategory, microscopic to macroscopic conversion factor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCategory Context triple: [Avogadro constant, isCategory, microscopic to macroscopic conversion factor]
-
A.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
B.
hasMajorCategory
Indicates that something is associated with or classified under a primary, overarching category.
-
C.
isAbout
Indicates that one entity has as its subject, focus, or primary concern the content, topic, or theme represented by another entity.
-
D.
hasNumberCategory
Indicates that an entity is associated with a specific numerical classification or type.
-
E.
isPartOfType
Indicates that one type or category is a constituent or subset within a larger, encompassing type or category.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.