Triple

T1734933
Position Surface form Disambiguated ID Type / Status
Subject Akkadian E37900 entity
Predicate languageCodeISO_639_2 P5197 FINISHED
Object akk 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: akk | Statement: [Akkadian, languageCodeISO_639_2, akk]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageCodeISO_639_2
Context triple: [Akkadian, languageCodeISO_639_2, akk]
  • A. languageCodeISO639-2 chosen
    Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
  • B. languageCodeISO639-1
    Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
  • C. sharesISO639-3CodeWith
    Indicates that two language entities share the same ISO 639-3 code, meaning they are treated as the same language in that coding system.
  • D. hasISO639_5Code
    Indicates that a language or language group is associated with a specific ISO 639-5 code that identifies it within the ISO 639-5 language classification standard.
  • E. hasISO6393Code
    Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab5c553e508190b0f511b05e07fa20 completed March 6, 2026, 10:59 p.m.
PD Predicate disambiguation batch_69aa61c25a648190892de94c997fb983 completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:30 p.m.