Triple
T27134971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | svedberg unit |
E681656
|
entity |
| Predicate | exactValueInSeconds |
P161888
|
FINISHED |
| Object | 1e-13 s |
—
|
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: 1e-13 s | Statement: [svedberg unit, exactValueInSeconds, 1e-13 s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exactValueInSeconds Context triple: [svedberg unit, exactValueInSeconds, 1e-13 s]
-
A.
exactValueKnownFor
Indicates that the precise, specific value of something is known and established for an entity in a given context.
-
B.
durationUntil
Indicates the length of time remaining from a given starting point until a specified future event or state occurs.
-
C.
timeIntervalLength
Indicates the duration or length of a specified time interval.
-
D.
timeEquivalentOf
Indicates that two temporal entities represent the same point in time or duration, possibly expressed in different formats or units.
-
E.
exactValueReason
Indicates that the value is specified exactly as given due to a particular justification or rationale.
- 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62479bbb88190bcad383443cbd638 |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61fa35ac48190890102c348ed81a0 |
completed | May 2, 2026, 4 p.m. |
Created at: April 27, 2026, 9:06 a.m.