Triple
T5150708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SI second |
E116185
|
entity |
| Predicate | constantExactness |
P62237
|
FINISHED |
| Object | exact by definition |
—
|
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: exact by definition | Statement: [SI second, constantExactness, exact by definition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: constantExactness Context triple: [SI second, constantExactness, exact by definition]
-
A.
exactFor
Indicates that one entity corresponds to or matches another entity with complete precision, without any deviation or approximation.
-
B.
constant
Indicates that the relationship or value does not change across different instances, contexts, or over time.
-
C.
precision
Indicates the degree to which an action, measurement, or outcome is carried out with exactness, minimal deviation, and fine-grained accuracy.
-
D.
exactValueReason
Indicates that the value is specified exactly as given due to a particular justification or rationale.
-
E.
accuracyDependsOn
Indicates that the accuracy of one entity or process is contingent upon, or influenced by, another entity or factor.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c1354c81908176703b4853c1a4 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b0fbb88190851e2d7ae1bdcc09 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79bf9b088190a556dc02f10204e4 |
completed | March 20, 2026, 4:45 p.m. |
Created at: March 20, 2026, 1:44 p.m.