Triple
T15134285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sundial |
E361511
|
entity |
| Predicate | canBeCorrectedTo |
P117449
|
FINISHED |
| Object | standard clock time |
—
|
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: standard clock time | Statement: [Sundial, canBeCorrectedTo, standard clock time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeCorrectedTo Context triple: [Sundial, canBeCorrectedTo, standard clock time]
-
A.
canBeCorrectedBy
Indicates that something has the potential to be made accurate, fixed, or improved through the intervention or action of a specified agent or method.
-
B.
includesCorrectionsFor
Indicates that one item contains modifications, fixes, or amendments that address errors or issues present in another item.
-
C.
requiresCorrection
Indicates that something is identified as needing modification, adjustment, or fixing to correct an error or deficiency.
-
D.
languageReform
Indicates efforts or actions aimed at changing, standardizing, or improving aspects of a language, such as its spelling, grammar, or usage rules.
-
E.
usesCorrectorType
Indicates that one entity applies or employs a corrector of the specified type in performing an action or process.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b29a4c819087f8818e3f5788f5 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:06 a.m.