Triple
T244357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avogadro constant |
E5003
|
entity |
| Predicate | hasExactValue |
P9774
|
FINISHED |
| Object | 6.02214076×10^23 |
—
|
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: 6.02214076×10^23 | Statement: [Avogadro constant, hasExactValue, 6.02214076×10^23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExactValue Context triple: [Avogadro constant, hasExactValue, 6.02214076×10^23]
-
A.
hasCommonValue
Indicates that two or more entities share at least one identical value or attribute in common.
-
B.
hasEquivalent
Indicates that two entities are considered equal in value, meaning, or function within a given context.
-
C.
hasMinimumValue
Indicates that an entity possesses a value that is the lowest permissible or observed within a specified set, range, or context.
-
D.
hasMaximumValue
Indicates that one value in a set is the greatest or highest possible according to a specified criterion.
-
E.
hasSingle
Indicates that an entity possesses exactly one instance of a specified related entity or attribute.
- 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_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. |
| PDg | Predicate description generation | batch_69a25dcba5148190ab80fd14c7cf4bb4 |
completed | Feb. 28, 2026, 3:15 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.