Triple
T1196319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Micromegas detectors |
E25675
|
entity |
| Predicate | hasTimeResolution |
P9092
|
FINISHED |
| Object | of order few nanoseconds |
—
|
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: of order few nanoseconds | Statement: [Micromegas detectors, hasTimeResolution, of order few nanoseconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimeResolution Context triple: [Micromegas detectors, hasTimeResolution, of order few nanoseconds]
-
A.
supportsTimescale
chosen
Indicates that one entity is capable of operating with, accommodating, or being compatible with a specified timescale or range of temporal resolutions.
-
B.
hasTimeStart
Indicates that an event, process, or state begins at a specific point in time.
-
C.
hasTimeOfDay
Indicates that a situation, event, or state occurs during, or is associated with, a specific part of the day (e.g., morning, afternoon, evening, night).
-
D.
hasClock
Indicates that one entity possesses, contains, or is equipped with a clock.
-
E.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd7a756c819085d695acfffeaceb |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5d40a08190b7682d8ef8075421 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.