Triple

T6790269
Position Surface form Disambiguated ID Type / Status
Subject Ghostscript E155913 entity
Predicate supportsFormat P203 FINISHED
Object JPEG E155901 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: JPEG | Statement: [Ghostscript, supportsFormat, JPEG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JPEG
Context triple: [Ghostscript, supportsFormat, JPEG]
  • A. JPEG chosen
    JPEG is a widely used digital image format that compresses photographic content to reduce file size while maintaining acceptable visual quality.
  • B. JPEG XR
    JPEG XR is an image compression standard developed by Microsoft that offers higher compression efficiency and support for high dynamic range and wide color gamut compared to traditional JPEG.
  • C. JPEG 2000
    JPEG 2000 is an image compression standard that improves on the original JPEG by using wavelet-based compression to provide higher quality, better scalability, and advanced features such as lossless compression and region-of-interest coding.
  • D. PNG
    PNG is the three-letter ISO 3166-1 alpha-3 country code representing Papua New Guinea.
  • E. PNG
    PNG (Portable Network Graphics) is a widely used raster image format known for its lossless compression and support for transparency, commonly used for web graphics and digital images.
  • 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_69c6881770fc8190972b2906390380f5 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2ab4ce88190b6311e4d5aac758c completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723cc35cc8190b5affdfd363171ba completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:15 p.m.