Triple

T3330327
Position Surface form Disambiguated ID Type / Status
Subject South Semitic languages E70016 entity
Predicate includesLanguage P2177 FINISHED
Object Sabaic E68213 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: Sabaic | Statement: [South Semitic languages, includesLanguage, Sabaic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabaic
Context triple: [South Semitic languages, includesLanguage, Sabaic]
  • A. Sabaic chosen
    Sabaic is an ancient South Arabian Semitic language once used in inscriptions and documents in what is now Yemen.
  • B. Sabaot
    Sabaot is a Southern Nilotic language spoken primarily by the Sabaot people in the Mount Elgon region of Kenya and Uganda.
  • C. Abasa
    Abasa is the 80th chapter of the Qur'an, known for its admonition regarding a moment when the Prophet Muhammad frowned at a blind man seeking guidance.
  • D. Sapian
    Sapian is a coastal municipality in the province of Capiz in the Philippines, known for its fishing industry and scenic bay.
  • E. Odias
    Odias are an Indo-Aryan ethnic group primarily associated with the Indian state of Odisha, known for their distinct Odia language and rich cultural and artistic traditions.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb171ee0881908642504ab0ac8329 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a810e2c8190bfc206bdeb1ac5b8 completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:12 p.m.