Triple
T31776282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SLC (single-level cell) |
E811072
|
entity |
| Predicate | hasReadSpeed |
P140228
|
FINISHED |
| Object | high read speed |
—
|
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: high read speed | Statement: [SLC (single-level cell), hasReadSpeed, high read speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReadSpeed Context triple: [SLC (single-level cell), hasReadSpeed, high read speed]
-
A.
readSpeed
chosen
Indicates the rate at which an entity reads or processes written material.
-
B.
hasReading
Indicates that an entity is associated with a particular reading, such as a measured value, interpretation, or recorded observation.
-
C.
hasServiceSpeed
Indicates that an entity provides a service operating at a specified speed or performance rate.
-
D.
hasClockSpeed
Indicates that an entity (typically a processor or device) operates at a specified clock frequency or speed.
-
E.
hasReadingType
Indicates that an entity is associated with a specific category or mode of reading, such as a particular interpretation, format, or type of reading measurement.
- 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_69f348e544a48190ab6e700b05f6438c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a01a18e350481909f848686568d19bc |
completed | May 11, 2026, 9:29 a.m. |
| PD | Predicate disambiguation | batch_6a01a121b67c81908a6c5be9eb8e9ca5 |
completed | May 11, 2026, 9:28 a.m. |
Created at: April 30, 2026, 11:35 p.m.