Triple

T14753406
Position Surface form Disambiguated ID Type / Status
Subject Time-Of-Flight detector E346669 entity
Predicate typicalTimeResolution P93350 FINISHED
Object order of 100 picoseconds 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: order of 100 picoseconds | Statement: [Time-Of-Flight detector, typicalTimeResolution, order of 100 picoseconds]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalTimeResolution
Context triple: [Time-Of-Flight detector, typicalTimeResolution, order of 100 picoseconds]
  • A. hasTemporalResolution chosen
    Indicates that one entity specifies the level of temporal detail or granularity at which another entity’s data, observation, or process is measured or represented.
  • B. typicalTimes
    Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
  • C. timeTravelGranularity
    Indicates the level of temporal precision or resolution at which time travel or time-based operations can occur between entities.
  • D. typicalPeriod
    Indicates the usual or characteristic time interval or duration associated with an event, process, or state.
  • E. timeCharacteristic
    Indicates a relationship where one entity specifies a temporal property, feature, or constraint that characterizes another entity or event.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d59df08190a86da5048358bd6e completed April 14, 2026, 11:03 p.m.
PD Predicate disambiguation batch_69de8bf9331481909582045cd567d91f completed April 14, 2026, 6:48 p.m.
Created at: April 10, 2026, 1:30 a.m.