Triple

T9312675
Position Surface form Disambiguated ID Type / Status
Subject APRALO E224041 entity
Predicate worksWith P398 FINISHED
Object ALAC E43496 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: ALAC | Statement: [APRALO, worksWith, ALAC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ALAC
Context triple: [APRALO, worksWith, ALAC]
  • A. ALAC chosen
    ALAC is the At-Large Advisory Committee within ICANN that represents the interests of individual Internet users in global domain name policy development.
  • B. ALAC
    ALAC (Apple Lossless Audio Codec) is Apple’s proprietary lossless audio compression format designed to reduce file size without sacrificing sound quality, commonly used in iTunes and Apple devices.
  • C. FLAC
    FLAC (Free Lossless Audio Codec) is an open-source audio compression format that reduces file size without any loss in sound quality, commonly used for high-fidelity music archiving and playback.
  • D. Monkey's Audio
    Monkey's Audio is a lossless audio compression format and codec known for its high compression ratios and Windows-focused software tools.
  • E. Dolby AC-4
    Dolby AC-4 is an advanced audio codec designed for next-generation broadcast and streaming, offering high-efficiency compression, immersive and personalized sound, and support for modern formats like UHD and HDR video services.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd20ae96e481909a1af9ea1c91f2b2 completed April 1, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c797640c8190be003e321faf3b86 completed April 4, 2026, 8:11 a.m.
Created at: March 30, 2026, 7:37 p.m.