Triple
T7229912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Planck units |
E154875
|
entity |
| Predicate | setsToOne |
P75747
|
FINISHED |
| Object | speed of light in vacuum c |
—
|
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: speed of light in vacuum c | Statement: [Planck units, setsToOne, speed of light in vacuum c]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setsToOne Context triple: [Planck units, setsToOne, speed of light in vacuum c]
-
A.
setsIn
Indicates that one entity places or positions another entity into or within a specified container, location, or context.
-
B.
sets
Indicates that an entity places, positions, or puts another entity into a particular state, location, or configuration.
-
C.
set
Indicates that an entity places, positions, or establishes another entity into a particular state, configuration, or location.
-
D.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
E.
settingRelation
Indicates a contextual relationship where one entity serves as the environment, backdrop, or situational context in which another entity exists or an event occurs.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea0d9b6c8190a0b5f0ab8d5cca19 |
completed | March 27, 2026, 8:35 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e8b5f6508190af28e06a7959d717 |
completed | March 27, 2026, 8:29 p.m. |
Created at: March 27, 2026, 2:54 p.m.