Triple

T13275838
Position Surface form Disambiguated ID Type / Status
Subject ISO 259 E316186 entity
Predicate hasPart P35 FINISHED
Object ISO 259-1 E316186 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: ISO 259-1 | Statement: [ISO 259, hasPart, ISO 259-1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ISO 259-1
Context triple: [ISO 259, hasPart, ISO 259-1]
  • A. ISO 259 chosen
    ISO 259 is an international standard that defines a systematic method for the transliteration of Hebrew characters into the Latin alphabet.
  • B. ISO 10589
    ISO 10589 is the international standard that defines the Intermediate System to Intermediate System (IS-IS) routing protocol used for exchanging routing information within an autonomous system.
  • C. ISO 7098
    ISO 7098 is an international standard that specifies the rules for the romanization of Chinese characters using the Hanyu Pinyin system.
  • D. ISO 15930
    ISO 15930 is an international standard that defines the PDF/X family of specifications for reliable, press-ready digital file exchange in the graphic arts and printing industries.
  • E. ISO 10957
    ISO 10957 is the international standard that defines the International Standard Music Number (ISMN) system used to uniquely identify printed music publications worldwide.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99042f56c819082440c89c0adc442 completed April 11, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a54ff488190a759b46963c0d842 completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:26 p.m.