Triple

T14342468
Position Surface form Disambiguated ID Type / Status
Subject ESWEEK E355636 entity
Predicate hasComponent P35 FINISHED
Object EMSOFT E978080 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: EMSOFT | Statement: [ESWEEK, hasComponent, EMSOFT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EMSOFT
Context triple: [ESWEEK, hasComponent, EMSOFT]
  • A. EMSOFT chosen
    EMSOFT is a leading international conference focused on research and advances in embedded software and systems.
  • B. Green Hills Software
    Green Hills Software is an American company specializing in high-reliability, safety- and security-focused embedded software development tools and real-time operating systems.
  • C. Eiffel Software
    Eiffel Software is a software company best known for developing the Eiffel programming language and tools that emphasize object-oriented design and software reliability.
  • D. VxWorks
    VxWorks is a real-time operating system (RTOS) widely used in embedded systems across industries such as aerospace, defense, telecommunications, and industrial automation.
  • E. Keil
    Keil is a German-origin surname borne by various notable individuals, including Portuguese composer Alfredo Keil.
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e87febc8190a63c668cbd0fd713 completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd469d899081909103563f209dd944 completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:14 a.m.