Triple
T23737342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RTK |
E586573
|
entity |
| Predicate | correctionDataType |
P153474
|
FINISHED |
| Object | differential corrections |
—
|
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: differential corrections | Statement: [RTK, correctionDataType, differential corrections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correctionDataType Context triple: [RTK, correctionDataType, differential corrections]
-
A.
correctionType
Indicates the specific kind or category of correction that has been applied to or associated with an entity or action.
-
B.
usesCorrectorType
Indicates that one entity applies or employs a corrector of the specified type in performing an action or process.
-
C.
datumType
Indicates the specific kind or category of data that characterizes or classifies a datum.
-
D.
requiresCorrection
Indicates that something is identified as needing modification, adjustment, or fixing to correct an error or deficiency.
-
E.
dataTypes
Indicates that one entity specifies or defines the kinds or formats of data that are valid or expected for another entity.
- 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_69e24907dc9c8190be074c9c96a0ec2d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bad356c88190ae29ce403145ee73 |
completed | April 29, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:10 p.m.