Triple
T25828813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Planck density |
E650603
|
entity |
| Predicate | approximateValueOrderOfMagnitude |
P9773
|
FINISHED |
| Object | 10^96 kg·m^−3 |
—
|
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: 10^96 kg·m^−3 | Statement: [Planck density, approximateValueOrderOfMagnitude, 10^96 kg·m^−3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateValueOrderOfMagnitude Context triple: [Planck density, approximateValueOrderOfMagnitude, 10^96 kg·m^−3]
-
A.
approximateSideLengthOrderOfMagnitude
Indicates that one entity’s side length is approximately the same order of magnitude as another entity’s side length, differing by no more than about a factor of ten.
-
B.
approximateEstimation
Indicates an estimation relationship where one value or assessment is only roughly or closely, but not exactly, equal to another.
-
C.
representsApproximately
Indicates that one entity serves as an inexact or close-but-not-exact representation or value of another entity.
-
D.
hasApproximateValue
chosen
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
-
E.
temperatureOrderOfMagnitude
Indicates that the temperatures of the related entities differ by approximately a specified order of magnitude (i.e., by a power-of-ten scale factor).
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 22, 2026, 7:37 a.m.