Triple
T36117021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GRW spontaneous collapse theory |
E1044638
|
entity |
| Predicate | typicalLocalizationWidth |
P19786
|
FINISHED |
| Object | about 10^-7 meters |
—
|
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: about 10^-7 meters | Statement: [GRW spontaneous collapse theory, typicalLocalizationWidth, about 10^-7 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLocalizationWidth Context triple: [GRW spontaneous collapse theory, typicalLocalizationWidth, about 10^-7 meters]
-
A.
typicalWidth
chosen
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
B.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
C.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
D.
availableWidth
Indicates the amount of horizontal space that is currently free or usable within a given context or container.
-
E.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.