Triple
T25717538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linky |
E644899
|
entity |
| Predicate | readingFrequency |
P77533
|
FINISHED |
| Object | automatic periodic readings |
—
|
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: automatic periodic readings | Statement: [Linky, readingFrequency, automatic periodic readings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readingFrequency Context triple: [Linky, readingFrequency, automatic periodic readings]
-
A.
oftenReadDuring
Indicates that something is frequently read or consulted during a particular time, activity, or situation.
-
B.
readSpeed
Indicates the rate at which an entity reads or processes written material.
-
C.
frequencyContent
chosen
Indicates that one entity specifies or characterizes the rate or frequency with which the content or occurrence of another entity takes place.
-
D.
readsTo
Indicates that one entity reads or recites content aloud for the benefit of another entity.
-
E.
reading
Indicates that an entity is engaged in the activity of interpreting and understanding written or printed material from another entity or source.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc6365288190ac46e37a887aa1e1 |
completed | May 2, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 9:46 p.m.