Triple

T1194423
Position Surface form Disambiguated ID Type / Status
Subject Aimaqs E25633 entity
Predicate selfDesignation P974 FINISHED
Object Aimaq E25633 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: Aimaq | Statement: [Aimaqs, selfDesignation, Aimaq]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aimaq
Context triple: [Aimaqs, selfDesignation, Aimaq]
  • A. Firozkohi Aimaqs
    Firozkohi Aimaqs are a Persian-speaking semi-nomadic ethnic group primarily inhabiting western and northwestern Afghanistan.
  • B. Aimaqs chosen
    The Aimaqs are a collection of semi-nomadic, Persian-speaking ethnic groups primarily inhabiting western and central Afghanistan.
  • C. Khora
    Khora is one of the now nearly extinct indigenous languages once spoken by the Great Andamanese people of the Andaman Islands in India.
  • D. Khashuri
    Khashuri is a town in central Georgia that serves as an important regional transport hub and gateway between eastern and western parts of the country.
  • E. Chelkash
    "Chelkash" is a short story by Russian writer Maksim Gorky that portrays a cynical dockside thief and explores themes of freedom, poverty, and moral ambiguity in late 19th-century Russia.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd78f61c8190bdba2255d35a8fe4 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f36371c8190a656463a9ae6402a completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:46 p.m.