Triple

T15434558
Position Surface form Disambiguated ID Type / Status
Subject FL Studio E369724 entity
Predicate notableInstrument P9123 FINISHED
Object FLEX E163328 NE 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: FLEX | Statement: [FL Studio, notableInstrument, FLEX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FLEX
Context triple: [FL Studio, notableInstrument, FLEX]
  • A. FLEX
    FLEX is a flexible, demand-responsive bus service operated by the North County Transit District in northern San Diego County, California.
  • B. Flex chosen
    Flex is an open-source software development framework originally created by Macromedia for building rich internet applications that run in the Adobe Flash Player.
  • C. flex
    flex is a widely used open-source lexical analyzer generator that processes patterns to produce C code for fast text scanning.
  • D. The Flex Project
    The Flex Project is the group responsible for maintaining and developing GNU Flex, a widely used open-source lexical analyzer generator.
  • E. LFLX
    LFLX is the ICAO airport code for Châteauroux-Centre "Marcel Dassault" Airport in central France, a facility known for cargo operations, aircraft maintenance, and pilot training.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03edb3ec481908b26164d4470c9bc completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21a5e55c81909801db54032589ac completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:21 a.m.