Triple
T11583941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | dark energy |
E274702
|
entity |
| Predicate | mayBeModeledAs |
P41880
|
FINISHED |
| Object | cosmological 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: cosmological constant | Statement: [dark energy, mayBeModeledAs, cosmological constant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeModeledAs Context triple: [dark energy, mayBeModeledAs, cosmological constant]
-
A.
possibleModel
chosen
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
B.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
C.
hasModeledCategory
Indicates that an entity has been modeled or classified according to a specific category or type within a defined schema or framework.
-
D.
mayAlsoBeProvidedAs
Indicates that something can optionally be supplied or made available in an alternative form or manner in addition to its primary provision.
-
E.
hasModelledFor
Indicates that one entity has served as a model for another entity, typically in a professional or representational context such as art, photography, or fashion.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8904db5748190ae5f10ae86ccdf46 |
completed | April 10, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.