Triple
T13527503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | double-slit experiment |
E323049
|
entity |
| Predicate | typicalSource |
P409
|
FINISHED |
| Object | light |
—
|
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: light | Statement: [double-slit experiment, typicalSource, light]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSource Context triple: [double-slit experiment, typicalSource, light]
-
A.
typicalSourceText
Indicates that the related entity is a common or representative textual source from which information, examples, or data about another entity are typically drawn.
-
B.
mainSourceType
Indicates the primary category or kind of source from which something originates or is derived.
-
C.
commonSources
Indicates that two or more entities share the same origin, cause, or source.
-
D.
typicalProgrammingSource
Indicates that one entity is a common or standard source from which the other entity obtains programming content or code.
-
E.
source
chosen
Indicates that something originates from, is derived from, or is provided by a particular entity or location.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafb8e0cc8190b47f6aeb8ced470e |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:44 p.m.