Triple

T1048613
Position Surface form Disambiguated ID Type / Status
Subject TW E22640 entity
Predicate notation P6184 FINISHED
Object Latin alphabet E368 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: Latin alphabet | Statement: [TW, notation, Latin alphabet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Latin alphabet
Context triple: [TW, notation, Latin alphabet]
  • A. Latin alphabet chosen
    The Latin alphabet is the writing system originally used for Latin that has become the most widely adopted script in the world, forming the basis of many modern languages including English, Spanish, and French.
  • B. Greek alphabet
    The Greek alphabet is an ancient writing system that originated in Greece and forms the basis of many modern European scripts, including the Latin alphabet.
  • C. Hebrew alphabet
    The Hebrew alphabet is an ancient consonant-based writing system used primarily for Hebrew and several other Jewish languages, including Judeo-Arabic and Yiddish.
  • D. Paleo-Latin alphabet
    The Paleo-Latin alphabet is an early form of the Latin writing system used on the Italian peninsula before the standardization of classical Latin script.
  • E. Arabic alphabet
    The Arabic alphabet is a cursive, right-to-left abjad script used across the Arab world and adapted for many other languages, including Persian, Urdu, and Pashto.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8b19a5c8190a532e025bd724088 completed March 1, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3ba9406c81909a13375fea05ee99 completed March 7, 2026, 2:52 p.m.
Created at: March 1, 2026, 7:42 p.m.