Triple
T1570591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cavendish experiment |
E33528
|
entity |
| Predicate | hasQuantity |
P27181
|
FINISHED |
| Object | gravitational constant |
—
|
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: gravitational constant | Statement: [Cavendish experiment, hasQuantity, gravitational constant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQuantity Context triple: [Cavendish experiment, hasQuantity, gravitational constant]
-
A.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
B.
hasKeyQuantity
chosen
Indicates that an entity is associated with a primary or defining quantity that characterizes or measures it.
-
C.
quantityType
Indicates that one entity is the type or category of quantity to which another entity (a specific measured or measurable amount) belongs.
-
D.
quantificationType
Indicates the specific kind or category of quantity or measurement being applied in a given context.
-
E.
hasNumberOfDrops
Indicates the quantity or count of drops associated with an entity or event.
- 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907ba63c88190b60c14dec8d1e40f |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.