Triple
T461794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | de Sitter spacetime |
E7354
|
entity |
| Predicate | hasConstant |
P9148
|
FINISHED |
| Object | Hubble parameter H |
—
|
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: Hubble parameter H | Statement: [de Sitter spacetime, hasConstant, Hubble parameter H]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConstant Context triple: [de Sitter spacetime, hasConstant, Hubble parameter H]
-
A.
includesConstant
Indicates that one entity contains or explicitly references a specific constant value within its definition or structure.
-
B.
usesConstant
chosen
Indicates that one entity makes use of a specific constant value defined or provided by another entity.
-
C.
constant
Indicates that the relationship or value does not change across different instances, contexts, or over time.
-
D.
hasDefinition
Indicates that one entity provides the meaning, explanation, or definition of another entity.
-
E.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede8eac081908dffade6a5e7950b |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.