Triple

T9340405
Position Surface form Disambiguated ID Type / Status
Subject Persian army E224750 entity
Predicate recruitmentFrom P4145 FINISHED
Object Saka E520877 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: Saka | Statement: [Persian army, recruitmentFrom, Saka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saka
Context triple: [Persian army, recruitmentFrom, Saka]
  • A. Saka
    Saka is an ancient Eastern Iranian language once spoken by the Saka people in the Tarim Basin region of Central Asia.
  • B. Sakaar
    Sakaar is a chaotic, trash-covered planet ruled by the Grandmaster in the Marvel Cinematic Universe, known for its gladiatorial contests and bizarre cosmic detritus.
  • C. Saka people chosen
    The Saka people were an ancient group of Eastern Iranian nomadic tribes of the Eurasian Steppe, culturally and linguistically related to the Scythians.
  • D. Shuka
    Shuka is a Japanese animation studio known for producing the later seasons and related works of the urban fantasy anime series Durarara!!.
  • E. Suo-Gân
    Suo-Gân is a traditional Welsh lullaby known for its gentle melody and soothing, lyrical character.
  • 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_69ca84286fcc81909f6e7fd7a7e862a2 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4bae2e2481909effc2dc89a642c5 completed April 1, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3f94ab88190a4c5a9129bd2ca14 completed April 4, 2026, 10:12 a.m.
Created at: March 30, 2026, 7:40 p.m.